Index

_ | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

_

__call__() (ClassifierFromVar method)
(Orange.associate.AssociationRulesInducer method)
(Orange.associate.AssociationRulesSparseInducer method)
(Orange.classification.Classifier method)
(Orange.classification.ConstantClassifier method)
(Orange.classification.Learner method)
(Orange.classification.bayes.NaiveClassifier method)
(Orange.classification.bayes.NaiveLearner method)
(Orange.classification.knn.FindNearest method)
(Orange.classification.knn.FindNearestConstructor method)
(Orange.classification.knn.kNNClassifier method)
(Orange.classification.knn.kNNLearner method)
(Orange.classification.logreg.LibLinearLogRegLearner method)
(Orange.classification.logreg.LogRegClassifier method)
(Orange.classification.logreg.LogRegFitter method)
(Orange.classification.logreg.LogRegLearner method)
(Orange.classification.neural.NeuralNetworkClassifier method)
(Orange.classification.neural.NeuralNetworkLearner method)
(Orange.classification.rules.CN2Classifier method)
(Orange.classification.rules.CN2UnorderedClassifier method)
(Orange.classification.rules.Orange.classification.rules.BeamFinder method)
(Orange.classification.rules.Orange.classification.rules.Evaluator method)
(Orange.classification.rules.Orange.classification.rules.Finder method)
(Orange.classification.rules.Orange.classification.rules.Rule method) , []
(Orange.classification.svm.RFE method)
(Orange.classification.svm.SVMLearner method)
(Orange.classification.svm.kernels.AdditionKernelWrapper method)
(Orange.classification.svm.kernels.CompositeKernelWrapper method)
(Orange.classification.svm.kernels.MultiplicationKernelWrapper method)
(Orange.classification.svm.kernels.PolyKernelWrapper method)
(Orange.classification.svm.kernels.RBFKernelWrapper method)
(Orange.classification.svm.kernels.SparseLinKernel method)
(Orange.classification.tree.C45Classifier method)
(Orange.classification.tree.Descender method)
(Orange.classification.tree.Pruner method)
(Orange.classification.tree.SplitConstructor method)
(Orange.classification.tree.Splitter method)
(Orange.classification.tree.StopCriteria method)
(Orange.classification.tree.TreeClassifier method)
(Orange.classification.tree.TreeLearner method)
(Orange.clustering.hierarchical.HierarchicalClustering method)
(Orange.clustering.kmeans.Clustering method)
(Orange.clustering.kmeans.init_hclustering method)
(Orange.data.filter.Filter method) , []
(Orange.data.sample.SubsetIndices method) , []
(Orange.distance.Distance method)
(Orange.distance.DistanceConstructor method)
(Orange.distance.MahalanobisDistance method)
(Orange.distance.PearsonRDistance method)
(Orange.distance.SpearmanRDistance method)
(Orange.ensemble.bagging.BaggedClassifier method)
(Orange.ensemble.bagging.BaggedLearner method)
(Orange.ensemble.boosting.BoostedClassifier method)
(Orange.ensemble.boosting.BoostedLearner method)
(Orange.ensemble.forest.RandomForestClassifier method)
(Orange.ensemble.forest.RandomForestLearner method)
(Orange.ensemble.forest.ScoreFeature method)
(Orange.feature.Descriptor method)
(Orange.feature.discretization.Discretization method)
(Orange.feature.imputation.ImputeClassifier method)
(Orange.feature.scoring.OrderAttributes method)
(Orange.feature.scoring.Score method) , [], [], []
(Orange.feature.selection.FilterAboveThreshold method)
(Orange.misc.Random method)
(Orange.multilabel.BRkNNClassifier method)
(Orange.multilabel.BinaryRelevanceClassifier method)
(Orange.multilabel.LabelPowersetClassifier method)
(Orange.multilabel.MLkNNClassifier method)
(Orange.projection.linear.Fda method)
(Orange.projection.linear.FreeViz method)
(Orange.projection.linear.PCA method)
(Orange.projection.linear.Projector method)
(Orange.projection.som.SOMMap method)
(Orange.projection.som.Solver method)
(Orange.regression.lasso.LassoRegression method)
(Orange.regression.lasso.LassoRegressionLearner method)
(Orange.regression.linear.LinearRegression method)
(Orange.regression.linear.LinearRegressionLearner method)
(Orange.regression.pls.PLSRegression method)
(Orange.regression.pls.PLSRegressionLearner method)
(Orange.regression.tree.TreeClassifier method)
(Orange.regression.tree.TreeLearner method)
(Orange.statistics.estimate.ConditionalByRows method)
(Orange.statistics.estimate.ConditionalEstimator method)
(Orange.statistics.estimate.ConditionalEstimatorByRows method)
(Orange.statistics.estimate.ConditionalEstimatorConstructor method)
(Orange.statistics.estimate.ConditionalEstimatorFromDistribution method)
(Orange.statistics.estimate.Estimator method)
(Orange.statistics.estimate.EstimatorConstructor method)
(Orange.statistics.estimate.EstimatorFromDistribution method)
(Orange.utils.ConsoleProgressBar method)
__getitem__() (Orange.clustering.hierarchical.HierarchicalCluster method)
(Orange.projection.som.Map method)
(Orange.projection.som.SOMMap method)
__init__() (Orange.associate.AssociationRule method) , [], []
(Orange.classification.ConstantClassifier method)
(Orange.classification.logreg.LibLinearLogRegLearner method)
(Orange.classification.svm.LinearSVMLearner method)
(Orange.classification.svm.MultiClassSVMLearner method)
(Orange.classification.svm.RFE method)
(Orange.classification.svm.SVMLearnerEasy method)
(Orange.classification.svm.ScoreSVMWeights method)
(Orange.clustering.kmeans.Clustering method)
(Orange.clustering.kmeans.init_hclustering method)
(Orange.data.Domain method) , [], [], [], [], [], []
(Orange.data.Instance method) , [], []
(Orange.data.Table method) , [], [], [], []
(Orange.data.Value method) , []
(Orange.data.sql.SQLReader method)
(Orange.data.sql.SQLWriter method)
(Orange.evaluation.testing.TestedExample method)
(Orange.feature.Continuous method)
(Orange.feature.Discrete method)
(Orange.feature.String method)
(Orange.feature.imputation.Defaults method) , []
(Orange.misc.SymMatrix method) , []
(Orange.projection.correspondence.CA method)
(Orange.regression.lasso.LassoRegressionLearner method)
(Orange.regression.linear.LinearRegression method)
(Orange.regression.linear.LinearRegressionLearner method)
(Orange.regression.pls.PLSRegressionLearner method)
(Orange.statistics.basic.Domain method)
(Orange.statistics.contingency.ClassVar method) , []
(Orange.statistics.contingency.Domain method)
(Orange.statistics.contingency.Table method)
(Orange.statistics.contingency.VarClass method) , []
(Orange.statistics.contingency.VarVar method)
(Orange.statistics.distribution.Continuous method) , [], []
(Orange.statistics.distribution.Discrete method) , [], []
(Orange.statistics.distribution.Distribution method)
(Orange.statistics.distribution.Domain method)
(Orange.statistics.distribution.Gaussian method) , []
(Orange.statistics.estimate.ConditionalLoess method)
(Orange.statistics.estimate.Kernel method)
(Orange.statistics.estimate.Loess method)
(Orange.statistics.estimate.M method)
(Orange.utils.ConsoleProgressBar method)
(Orange.utils.counters.BooleanCounter method)
(Orange.utils.counters.CanonicFuncCounter method)
(Orange.utils.counters.LimitedCounter method)
(Orange.utils.counters.MofNCounter method)
(Orange.utils.counters.NondecreasingCounter method)
(Orange.utils.serverfiles.ServerFiles method)
(OrangeWidgets.plot.owpoint.OWPoint method)
__iter__() (Orange.projection.som.Map method)
(Orange.projection.som.SOMMap method)
__len__() (Orange.clustering.hierarchical.HierarchicalCluster method)
__str__() (Orange.classification.bayes.NaiveClassifier method)

A

above_threshold() (Orange.feature.selection static method)
abs (Orange.statistics.distribution.Distribution attribute)
(Orange.statistics.distribution.Gaussian attribute)
accept_special (Orange.data.filter.ValueFilter attribute)
add() (Orange.evaluation.testing.ExperimentResults method)
(Orange.statistics.basic.Variable method)
(Orange.statistics.contingency.Table method)
(Orange.statistics.distribution.Distribution method)
add_axis() (OrangeWidgets.plot.owplot.OWPlot method)
add_curve() (OrangeWidgets.plot.owlegend.OWLegend method)
(OrangeWidgets.plot.owplot.OWPlot method)
add_custom_axis() (OrangeWidgets.plot.owplot.OWPlot method)
add_custom_curve() (OrangeWidgets.plot.owplot.OWPlot method)
add_item() (OrangeWidgets.plot.owlegend.OWLegend method)
(OrangeWidgets.plot.owplot.OWPlot method)
add_marker() (OrangeWidgets.plot.owplot.OWPlot method)
add_meta() (Orange.data.Domain method)
add_meta_attribute() (Orange.data.Table method)
add_metas() (Orange.data.Domain method)
add_result() (Orange.evaluation.testing.TestedExample method)
add_value() (Orange.feature.Discrete method)
add_var_class() (Orange.statistics.contingency.Class method)
AdditionKernelWrapper (class in Orange.classification.svm.kernels)
addToolTip() (OrangeWidgets.plot.owtools.TooltipManager method)
adjust_decimals (Orange.feature.Continuous attribute)
adjust_threshold (Orange.classification.bayes.NaiveClassifier attribute)
(Orange.classification.bayes.NaiveLearner attribute)
advance() (Orange.utils.ConsoleProgressBar method)
agglomerative clustering
aglomerative clustering
algorithm (Orange.regression.pls.PLSRegressionLearner attribute)
allinfo() (in module Orange.utils.serverfiles)
(Orange.utils.serverfiles.ServerFiles method)
alpha() (Orange.projection.som.Solver method)
alpha_value_slider() (OrangeWidgets.plot.OWPlotGUI method)
animations_check_box() (OrangeWidgets.plot.OWPlotGUI method)
antialiasing_check_box() (OrangeWidgets.plot.OWPlotGUI method)
AP() (in module Orange.evaluation.scoring)
append() (Orange.data.Table method)
applies_both() (Orange.associate.AssociationRule method)
applies_left() (Orange.associate.AssociationRule method)
applies_right() (Orange.associate.AssociationRule method)
apriori_distribution (Orange.classification.majority.MajorityLearner attribute)
AssociationRule (class in Orange.associate)
AssociationRulesInducer (class in Orange.associate)
AssociationRulesSparseInducer (class in Orange.associate)
AsValue (class in Orange.feature.imputation)
AsValueConstructor (class in Orange.feature.imputation)
attach() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
attract_g (Orange.projection.linear.FreeViz attribute)
attribute_load_status (Orange.data.Table attribute)
attributes (Orange.feature.Descriptor attribute)
AUC() (in module Orange.evaluation.scoring)
AUC_for_single_class() (in module Orange.evaluation.scoring)
AUC_matrix() (in module Orange.evaluation.scoring)
AUCWilcoxon() (in module Orange.evaluation.scoring)
AVERAGE (in module Orange.clustering.hierarchical)
average (NormalizeContinuous attribute)
average() (Orange.statistics.distribution.Continuous method)
(Orange.statistics.distribution.Gaussian method)
avg (Orange.statistics.basic.Variable attribute)
avg_linkage() (Orange.misc.SymMatrix method)
avg_stress (Orange.projection.mds.MDS attribute)
axes() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
axis_margin (OrangeWidgets.plot.owplot.OWPlot attribute)

B

BaggedClassifier (class in Orange.ensemble.bagging)
BaggedLearner (class in Orange.ensemble.bagging)
bagging
base_class (Orange.evaluation.testing.ExperimentResults attribute)
base_classifier (Orange.feature.imputation.ImputeClassifier attribute)
base_learner (Orange.feature.imputation.ImputeLearner attribute)
base_value (Orange.feature.Discrete attribute)
BaseRegressionLearner (class in Orange.regression.base)
Basic Statistics for Continuous Features
batch (Orange.classification.tree.C45Learner attribute)
best_threshold() (Orange.feature.scoring.Score method)
bestN() (in module Orange.data.preprocess)
BestOnTheFly (class in Orange.utils.selection)
bestP() (in module Orange.data.preprocess)
beta (Orange.classification.logreg.LogRegClassifier attribute)
beta_se (Orange.classification.logreg.LogRegClassifier attribute)
bias (Orange.classification.svm.LinearClassifier attribute)
BiModal (class in Orange.feature.discretization)
BiModalDiscretizer (class in Orange.feature.discretization)
binarization (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
Binary Relevance Classifier
Binary Relevance Learner , []
BinaryRelevanceClassifier (class in Orange.multilabel)
BinaryRelevanceLearner (class in Orange.multilabel)
biplot() (Orange.projection.linear.PcaProjector method)
BooleanCounter (class in Orange.utils.counters)
BoostedClassifier (class in Orange.ensemble.boosting)
BoostedLearner (class in Orange.ensemble.boosting)
boosting
both_special_dist() (Orange.distance.EuclideanDistance method)
BR-kNN Learner , []
branch (Orange.classification.tree.C45Node attribute)
branch_descriptions (Orange.classification.tree.Node attribute)
branch_selector (Orange.classification.tree.Node attribute)
branch_sizes (Orange.classification.tree.Node attribute)
branches (Orange.classification.tree.Node attribute)
(Orange.clustering.hierarchical.HierarchicalCluster attribute)
Brier_score() (in module Orange.evaluation.scoring)
BRkNN Classifier
BRkNNClassifier (class in Orange.multilabel)
BRkNNLearner (class in Orange.multilabel)
burt_table() (in module Orange.projection.correspondence)
button() (in module OWGUI)
by (in module Orange.classification.tree)
by_whom() (in module Orange.classification.tree)

C

C (Orange.regression.pls.PLSRegression attribute)
C45Classifier (class in Orange.classification.tree)
C45Learner (class in Orange.classification.tree)
C45Node (class in Orange.classification.tree)
CA (class in Orange.projection.correspondence)
CA() (in module Orange.evaluation.scoring)
calc_distance() (Orange.projection.mds.MDS method)
calc_stress() (Orange.projection.mds.MDS method)
cancel_all_updates() (Orange.OrangeWidgets.plot.owcurve.OWCurve method)
candidate_selector (Orange.classification.rules.Orange.classification.rules.BeamFinder attribute)
CanonicFuncCounter (class in Orange.utils.counters)
case_sensitive (Orange.data.filter.ValueFilterString attribute)
(Orange.data.filter.ValueFilterStringList attribute)
cases (Orange.statistics.distribution.Distribution attribute)
center (Orange.projection.linear.Projector attribute)
centroids (Orange.clustering.kmeans.Clustering attribute)
cf (Orange.classification.tree.C45Learner attribute)
check (Orange.data.filter.IsDefined attribute)
check_cached_data (Orange.feature.scoring.Relief attribute)
checkBox() (in module OWGUI)
checksum() (Orange.data.Table method)
checkWithSpin() (in module OWGUI)
CircleCurve (class in OrangeWidgets.plot.owtools)
Class (class in Orange.statistics.contingency)
class_dist (Orange.classification.tree.C45Node attribute)
class_distribution (Orange.classification.rules.Orange.classification.rules.Rule attribute)
class_is_outer (Orange.statistics.contingency.Domain attribute)
class_name (Orange.data.sql.SQLReader attribute)
class_values (Orange.evaluation.testing.ExperimentResults attribute)
class_var (Orange.classification.ConstantClassifier attribute)
(Orange.data.Domain attribute)
(Orange.misc.CostMatrix attribute)
class_vars (Orange.data.Domain attribute)
classes (Orange.evaluation.testing.TestedExample attribute)
(Orange.statistics.contingency.Domain attribute)
classification
CN2
CN2-SD
accuracy
area under ROC
classifier
data table
k-nearest neighbors
learner
logistic regression
lookup
lookup table
majority classifier
naive Bayes classifier
naive Bayesian classifier
rule induction
scoring
tree
trees
unordered CN2
classification tree
classification trees
pruning
classification_rules (Orange.associate.AssociationRulesInducer attribute)
Classifier (class in Orange.classification)
classifier (Orange.classification.rules.Orange.classification.rules.Rule attribute)
(Orange.tuning.ThresholdClassifier attribute)
classifier_for_unknown (Orange.classification.lookup.ClassifierByDataTable attribute)
classifier_names (Orange.evaluation.testing.ExperimentResults attribute)
ClassifierByDataTable (class in Orange.classification.lookup)
ClassifierByLookupTable (class in Orange.classification.lookup)
ClassifierByLookupTable1 (class in Orange.classification.lookup)
ClassifierByLookupTable2 (class in Orange.classification.lookup)
ClassifierByLookupTable3 (class in Orange.classification.lookup)
ClassifierFromVar (built-in class)
ClassifierFromVarFD (built-in class)
classifiers
in Python
classifiers (Orange.evaluation.testing.ExperimentResults attribute)
ClassVar (class in Orange.statistics.contingency)
classVar (Orange.statistics.contingency.Class attribute)
clear() (Orange.utils.ConsoleProgressBar method)
(OrangeWidgets.plot.owlegend.OWLegend method)
clone() (in module Orange.clustering.hierarchical)
cluster_depths() (in module Orange.clustering.hierarchical)
cluster_to_list() (in module Orange.clustering.hierarchical)
clustering
Clustering (class in Orange.clustering.kmeans)
clustering() (in module Orange.clustering.hierarchical)
clustering, hierarchical, dendrogram
clustering, kmeans
clustering_features() (in module Orange.clustering.hierarchical)
clusters (Orange.clustering.kmeans.Clustering attribute)
CN2-SD
CN2Classifier (class in Orange.classification.rules)
CN2EVCUnorderedLearner (class in Orange.classification.rules)
CN2Learner (class in Orange.classification.rules)
CN2SDUnorderedLearner (class in Orange.classification.rules)
CN2UnorderedClassifier (class in Orange.classification.rules)
CN2UnorderedLearner (class in Orange.classification.rules)
coef0 (Orange.regression.lasso.LassoRegression attribute)
coefficients (Orange.regression.lasso.LassoRegression attribute)
(Orange.regression.linear.LinearRegression attribute)
coefs (Orange.regression.pls.PLSRegression attribute)
color() (OrangeWidgets.plot.owpoint.OWPoint method)
column_factors() (Orange.projection.correspondence.CA method)
column_inertia() (Orange.projection.correspondence.CA method)
column_principal_axes (Orange.projection.correspondence.CA attribute)
column_profiles() (Orange.projection.correspondence.CA method)
comboBox() (in module OWGUI)
commandline() (Orange.classification.tree.C45Learner method)
compare (Orange.tuning.TuneParameters attribute)
compare_bigger() (in module Orange.utils.selection)
compare_first_bigger() (in module Orange.utils.selection)
compare_first_smaller() (in module Orange.utils.selection)
compare_last_bigger() (in module Orange.utils.selection)
compare_last_smaller() (in module Orange.utils.selection)
compare_smaller() (in module Orange.utils.selection)
compatible() (Orange.data.Instance method)
COMPLETE (in module Orange.clustering.hierarchical)
complexity (Orange.classification.rules.Orange.classification.rules.Rule attribute)
CompositeKernelWrapper (class in Orange.classification.svm.kernels)
compute_CD() (in module Orange.evaluation.scoring)
compute_centeroid() (Orange.clustering.kmeans.Clustering method)
compute_cluster() (Orange.clustering.kmeans.Clustering method)
compute_cond() (Orange.multilabel.MLkNNLearner method)
compute_friedman() (in module Orange.evaluation.scoring)
compute_prior() (Orange.multilabel.MLkNNLearner method)
compute_ROC() (in module Orange.evaluation.scoring)
compute_value() (Orange.feature.Descriptor method)
computes_thresholds (Orange.feature.scoring.Score attribute)
conditional_distributions (Orange.classification.bayes.NaiveClassifier attribute)
conditional_estimator_constructor (Orange.classification.bayes.NaiveLearner attribute)
(Orange.feature.scoring.ScoreFromProbabilities attribute)
conditional_estimator_constructor_continuous (Orange.classification.bayes.NaiveLearner attribute)
conditional_estimators (Orange.classification.bayes.NaiveClassifier attribute)
ConditionalByRows (class in Orange.statistics.estimate)
ConditionalEstimator (class in Orange.statistics.estimate)
ConditionalEstimatorByRows (class in Orange.statistics.estimate)
ConditionalEstimatorConstructor (class in Orange.statistics.estimate)
ConditionalEstimatorFromDistribution (class in Orange.statistics.estimate)
ConditionalLoess (class in Orange.statistics.estimate)
conditions (Orange.data.filter.Values attribute)
confidence (Orange.associate.AssociationRule attribute)
(Orange.associate.AssociationRulesInducer attribute)
(Orange.associate.AssociationRulesSparseInducer attribute)
confusion_chi_square() (in module Orange.evaluation.scoring)
confusion_matrices() (in module Orange.evaluation.scoring)
ConfusionMatrix (class in Orange.evaluation.scoring)
conjunction (Orange.data.filter.Values attribute)
connect() (Orange.data.sql.SQLReader method)
(Orange.data.sql.SQLWriter method)
consensus_matrix() (in module Orange.clustering.consensus)
ConsoleProgressBar (class in Orange.utils)
Constant (Orange.classification.logreg.LogRegFitter attribute)
ConstantClassifier (class in Orange.classification)
construct_variable() (Orange.feature.discretization.Discretizer method)
Constructor (class in Orange.feature.imputation)
contingency (Orange.classification.tree.Node attribute)
Contingency table
Contingency_Class (Orange.feature.scoring.Score attribute)
contingency_computer (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
Continuize (class in Orange.data.preprocess)
continuize_table() (Orange.regression.base.BaseRegressionLearner method)
Continuous (class in Orange.feature)
(class in Orange.statistics.distribution)
continuous_palette (OrangeWidgets.plot.owplot.OWPlot attribute)
cophenetic_correlation() (in module Orange.clustering.hierarchical)
cophenetic_distances() (in module Orange.clustering.hierarchical)
Cost (class in Orange.feature.scoring)
cost (Orange.feature.scoring.Cost attribute)
CostMatrix (class in Orange.misc)
CostMatrix() (Orange.misc.CostMatrix method) , [], []
count_leaves() (Orange.classification.tree.TreeClassifier method)
(Orange.regression.tree.TreeClassifier method)
count_nodes() (Orange.classification.tree.TreeClassifier method)
(Orange.regression.tree.TreeClassifier method)
cover_and_remove (Orange.classification.rules.Orange.classification.rules.RuleLearner attribute)
coverage (Orange.associate.AssociationRule attribute)
CovererAndRemover_AddWeights (class in Orange.classification.rules)
CovererAndRemover_MultWeights (class in Orange.classification.rules)
create() (Orange.data.sql.SQLWriter method)
create_anchors() (Orange.data.preprocess.scaling.ScaleLinProjData method)
(Orange.data.preprocess.scaling.ScaleLinProjData3D method)
create_box() (OrangeWidgets.plot.OWPlotGUI method)
create_domain() (Orange.utils.serverfiles.ServerFiles method)
create_projection_as_example_table() (Orange.data.preprocess.scaling.ScaleLinProjData method)
(Orange.data.preprocess.scaling.ScaleLinProjData3D method)
(Orange.data.preprocess.scaling.ScaleScatterPlotData method)
create_projection_as_example_table_3D() (Orange.data.preprocess.scaling.ScaleScatterPlotData method)
createAnchors() (Orange.data.preprocess.scaling.ScaleLinProjData method)
(Orange.data.preprocess.scaling.ScaleLinProjData3D method)
createProjectionAsExampleTable() (Orange.data.preprocess.scaling.ScaleLinProjData method)
(Orange.data.preprocess.scaling.ScaleLinProjData3D method)
(Orange.data.preprocess.scaling.ScaleScatterPlotData method)
createProjectionAsExampleTable3D() (Orange.data.preprocess.scaling.ScaleScatterPlotData method)
cross-validation
cross_validation() (Orange.evaluation.testing.Evaluation method)
cut (Orange.classification.tree.C45Node attribute)

D

data
class
discretization
domain
examples
features
input
instances
missing values
subsetting
data (Orange.clustering.kmeans.Clustering attribute)
(Orange.tuning.TuneParameters attribute)
data mining
supervised
data scaling
data() (Orange.data.sql.SQLReader method)
(Orange.OrangeWidgets.plot.owcurve.OWCurve method)
data_description (Orange.classification.lookup.ClassifierByLookupTable attribute)
data_matrix (Orange.projection.correspondence.CA attribute)
data_rect() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
data_stopping (Orange.classification.rules.Orange.classification.rules.RuleLearner attribute)
ddof (Orange.projection.linear.PCA attribute)
default_distribution (Orange.classification.ConstantClassifier attribute)
default_meta_id (Orange.feature.Descriptor attribute)
default_val (Orange.classification.ConstantClassifier attribute)
Defaults (class in Orange.feature.imputation)
defaults (Orange.feature.imputation.AsValue attribute)
(Orange.feature.imputation.Defaults attribute)
deflation_mode (Orange.regression.pls.PLSRegressionLearner attribute)
dendrogram_draw() (in module Orange.clustering.hierarchical)
dendrogram_layout() (in module Orange.clustering.hierarchical)
density() (Orange.statistics.distribution.Continuous method)
(Orange.statistics.distribution.Gaussian method)
deprecated_attribute() (in module Orange.utils)
deprecated_function_name() (in module Orange.utils)
deprecated_keywords() (in module Orange.utils)
deprecated_members() (in module Orange.utils)
deprecation_warning() (in module Orange.utils)
Descender (class in Orange.classification.tree)
descender (Orange.classification.tree.TreeClassifier attribute)
(Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeClassifier attribute)
(Orange.regression.tree.TreeLearner attribute)
Descender_UnknownMergeAsBranchSizes (class in Orange.classification.tree)
Descender_UnknownMergeAsSelector (class in Orange.classification.tree)
Descender_UnknownToBranch (class in Orange.classification.tree)
Descender_UnknownToCommonBranch (class in Orange.classification.tree)
Descender_UnknownToCommonSelector (class in Orange.classification.tree)
Descender_UnknownToNode (class in Orange.classification.tree)
Descriptor (class in Orange.feature)
Descriptor.make() (in module Orange.feature)
Descriptor.MakeStatus.Incompatible (in module Orange.feature)
Descriptor.MakeStatus.MissingValues (in module Orange.feature)
Descriptor.MakeStatus.NoRecognizedValues (in module Orange.feature)
Descriptor.MakeStatus.NotFound (in module Orange.feature)
Descriptor.MakeStatus.OK (in module Orange.feature)
Descriptor.retrieve() (in module Orange.feature)
detach() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
deterministic (Orange.feature.imputation.Random attribute)
dev (Orange.statistics.basic.Variable attribute)
dev() (Orange.statistics.distribution.Continuous method)
(Orange.statistics.distribution.Gaussian method)
dict_model (Orange.regression.linear.LinearRegression attribute)
dim (Orange.misc.SymMatrix attribute)
(Orange.projection.mds.MDS attribute)
dimension (Orange.misc.CostMatrix attribute)
disconnect() (Orange.data.sql.SQLReader method)
(Orange.data.sql.SQLWriter method)
Discrete (class in Orange.feature)
(class in Orange.statistics.distribution)
Discrete2Continuous (built-in class)
discrete_names (Orange.data.sql.SQLReader attribute)
discrete_palette (OrangeWidgets.plot.owplot.OWPlot attribute)
discretization , []
Discretization (class in Orange.feature.discretization)
discretize_domain() (in module Orange.data.preprocess.scaling)
DiscretizeEntropy (class in Orange.data.preprocess)
Discretizer (class in Orange.feature.discretization)
DiscretizeTable (class in Orange.data.discretization)
Distance (class in Orange.distance)
(class in Orange.feature.scoring)
distance (Orange.classification.knn.FindNearest attribute)
distance_constructor (Orange.classification.knn.FindNearestConstructor attribute)
(Orange.classification.knn.kNNLearner attribute)
distance_ID (Orange.classification.knn.FindNearest attribute)
distance_matrix() (in module Orange.distance)
(Orange.data.outliers.OutlierDetection method)
DistanceConstructor (class in Orange.distance)
DistanceNormalized (class in Orange.distance)
distances (Orange.projection.mds.MDS attribute)
Distribution (class in Orange.statistics.distribution)
distribution (Orange.classification.bayes.NaiveClassifier attribute)
(Orange.classification.tree.Node attribute)
distribution_for_unknown (ClassifierFromVar attribute)
(ClassifierFromVarFD attribute)
Distributions
distributions (Orange.classification.lookup.ClassifierByLookupTable attribute)
distributions() (Orange.distance.EuclideanDistance method)
Divergence (Orange.classification.logreg.LogRegFitter attribute)
Domain (class in Orange.data)
(class in Orange.statistics.basic)
(class in Orange.statistics.contingency)
(class in Orange.statistics.distribution)
domain (ClassifierFromVarFD attribute)
(Orange.data.Instance attribute)
(Orange.data.Table attribute)
(Orange.data.filter.Filter attribute)
(Orange.data.sql.SQLReader attribute)
(Orange.feature.imputation.AsValue attribute)
domain_version (Orange.distance.DistanceNormalized attribute)
DomainContingency (Orange.feature.scoring.Score attribute)
DomainContinuizer (class in Orange.data.continuization)
dont_impute_classifier (Orange.feature.imputation.ImputeLearner attribute)
dot() (Orange.classification.tree.TreeClassifier method)
(Orange.regression.tree.TreeClassifier method)
download() (in module Orange.utils.serverfiles)
(Orange.utils.serverfiles.ServerFiles method)
downloadFH() (Orange.utils.serverfiles.ServerFiles method)
DualKernelWrapper (class in Orange.classification.svm.kernels)
dump() (in module Orange.classification.logreg)
dump_lookup_function() (in module Orange.classification.lookup)

E

eigen_values (Orange.projection.linear.FdaProjector attribute)
eigen_vectors (Orange.projection.linear.FdaProjector attribute)
ensemble
boosting
ensemble
random forest
stacking
ensembles
bagging
boosting
random forests
stacking
Entropy (class in Orange.feature.discretization)
EqualFreq (class in Orange.feature.discretization)
EqualWidth (class in Orange.feature.discretization)
EqualWidthDiscretizer (class in Orange.feature.discretization)
error() (Orange.statistics.distribution.Continuous method)
Estimator (class in Orange.statistics.estimate)
estimator (Orange.classification.bayes.NaiveClassifier attribute)
estimator_constructor (Orange.classification.bayes.NaiveLearner attribute)
(Orange.classification.majority.MajorityLearner attribute)
(Orange.feature.scoring.ScoreFromProbabilities attribute)
(Orange.statistics.estimate.ConditionalByRows attribute)
estimator_list (Orange.statistics.estimate.ConditionalEstimatorByRows attribute)
EstimatorConstructor (class in Orange.statistics.estimate)
EstimatorFromDistribution (class in Orange.statistics.estimate)
Euclidean (class in Orange.distance)
EuclideanDistance (class in Orange.distance)
evaluate (Orange.tuning.TuneParameters attribute)
Evaluation (class in Orange.evaluation.testing)
execute() (Orange.data.sql.SQLReader method)
ExperimentResults (class in Orange.evaluation.testing)
ext (Orange.multilabel.brknn.BRkNNLearner attribute)
extend() (Orange.data.Table method)

F

F (Orange.regression.linear.LinearRegression attribute)
F1() (in module Orange.evaluation.scoring)
factor (Ordinal2Continuous attribute)
Falpha() (in module Orange.evaluation.scoring)
FDA
Fda (class in Orange.projection.linear)
FdaProjector (class in Orange.projection.linear)
feature
discretization
feature scoring
feature selection
selection
value imputation
feature construction
lookup classifiers
feature scoring
ReliefF
cost
gain ratio
gini index
information gain
mean square error
relevance
feature selection
feature_distance_matrix() (in module Orange.clustering.hierarchical)
feature_distances() (Orange.distance.DistanceNormalized method)
features (Orange.data.Domain attribute)
FeatureSelection (class in Orange.data.preprocess)
filter
Filter (class in Orange.data.filter)
filter (Orange.classification.rules.Orange.classification.rules.Rule attribute)
filter() (Orange.data.Table method) , []
filter_and_store() (Orange.classification.rules.Orange.classification.rules.Rule method)
filter_bool() (Orange.data.Table method)
filter_ref() (Orange.data.Table method)
FilterAboveThreshold (class in Orange.feature.selection)
FilterBestN (class in Orange.feature.selection)
FilterConjunction (class in Orange.data.filter)
FilterDisjunction (class in Orange.data.filter)
FilteredClassifier (class in Orange.feature.selection)
FilteredLearner (class in Orange.feature.selection)
filtering
instance filtering
FilterRelief (class in Orange.feature.selection)
filters (Orange.data.filter.FilterConjunction attribute)
(Orange.data.filter.FilterDisjunction attribute)
find_nearest (Orange.classification.knn.kNNClassifier attribute)
FindNearest (class in Orange.classification.knn)
FindNearestConstructor (class in Orange.classification.knn)
finish() (Orange.utils.ConsoleProgressBar method)
first (Orange.clustering.hierarchical.HierarchicalCluster attribute)
first_cut (Orange.feature.discretization.EqualWidthDiscretizer attribute)
Fisher Discriminant Analysis
fista() (Orange.regression.lasso.LassoRegressionLearner method)
fit() (Orange.regression.pls.PLSRegressionLearner method)
fit_status (Orange.classification.logreg.LogRegClassifier attribute)
fitted (Orange.regression.linear.LinearRegression attribute)
folds (Orange.data.sample.SubsetIndicesCV attribute)
(Orange.tuning.TuneParameters attribute)
force_attribute (Orange.feature.discretization.Entropy attribute)
force_balancing (Orange.projection.linear.FreeViz attribute)
force_sigma (Orange.projection.linear.FreeViz attribute)
FreeViz (class in Orange.projection.linear)
FreeVizClassifier (class in Orange.projection.linear)
FreeVizLearner (class in Orange.projection.linear)
fs (in module Orange.classification.tree)

G

gain_ratio (Orange.classification.tree.C45Learner attribute)
GainRatio (class in Orange.feature.scoring)
Gaussian (class in Orange.statistics.distribution)
Generator (Orange.feature.scoring.Score attribute)
get_best_matching_node() (Orange.projection.som.SOMMap method)
get_bootstrap_sample() (in module Orange.regression.lasso)
get_class() (Orange.data.Instance method)
get_classes() (Orange.data.Instance method)
get_index() (Orange.classification.lookup.ClassifierByLookupTable method)
get_items() (Orange.data.Table method)
get_items_ref() (Orange.data.Table method)
get_itemsets() (Orange.associate.AssociationRulesInducer method)
(Orange.associate.AssociationRulesSparseInducer method)
get_KNN() (Orange.misc.SymMatrix method)
get_labels_a() (Orange.multilabel.BRkNNClassifier method)
get_labels_b() (Orange.multilabel.BRkNNClassifier method)
get_linear_svm_weights() (Orange.classification.svm static method)
get_lipschitz() (Orange.regression.lasso.LassoRegressionLearner method)
get_meta() (Orange.data.Domain method)
get_metas() (Orange.data.Domain method) , []
(Orange.data.Instance method) , []
get_prob() (Orange.multilabel.BRkNNClassifier method)
get_projected_point_position() (Orange.data.preprocess.scaling.ScaleLinProjData method)
(Orange.data.preprocess.scaling.ScaleLinProjData3D method)
(Orange.data.preprocess.scaling.ScaleScatterPlotData method)
get_valid_indices() (Orange.data.preprocess.scaling.ScaleData method)
get_valid_list() (Orange.data.preprocess.scaling.ScaleData method)
get_valid_subset_indices() (Orange.data.preprocess.scaling.ScaleData method)
get_valid_subset_list() (Orange.data.preprocess.scaling.ScaleData method)
get_value_from (Orange.feature.Descriptor attribute)
get_values() (Orange.misc.SymMatrix method)
get_variable_value_indices() (in module Orange.data.preprocess.scaling)
get_variable_values_sorted() (in module Orange.data.preprocess.scaling)
get_weight() (Orange.data.Instance method)
get_xy_data_positions() (Orange.data.preprocess.scaling.ScaleScatterPlotData method)
get_xy_subset_data_positions() (Orange.data.preprocess.scaling.ScaleScatterPlotData method)
getAttributeIcons() (in module OWGUI)
getClassDistribution() (in module Orange.statistics.distribution)
getcost() (Orange.misc.CostMatrix method)
getProjectedPointPosition() (Orange.data.preprocess.scaling.ScaleLinProjData method)
(Orange.data.preprocess.scaling.ScaleLinProjData3D method)
(Orange.data.preprocess.scaling.ScaleScatterPlotData method)
getstring() (Orange.utils.ConsoleProgressBar method)
getValidIndices() (Orange.data.preprocess.scaling.ScaleData method)
getValidList() (Orange.data.preprocess.scaling.ScaleData method)
getValidSubsetIndices() (Orange.data.preprocess.scaling.ScaleData method)
getValidSubsetList() (Orange.data.preprocess.scaling.ScaleData method)
getXYDataPositions() (Orange.data.preprocess.scaling.ScaleScatterPlotData method)
getXYSubsetDataPositions() (Orange.data.preprocess.scaling.ScaleScatterPlotData method)
Gini (class in Orange.feature.scoring)
graph_ranks() (in module Orange.evaluation.scoring)
graph_transform() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
gui (OrangeWidgets.plot.owplot.OWPlot attribute)

H

Hamming (class in Orange.distance)
HammingDistance (class in Orange.distance)
handles_continuous (Orange.feature.scoring.Score attribute)
handles_discrete (Orange.feature.scoring.Score attribute)
has_attribute() (Orange.data.Domain method)
has_continuous_attributes() (Orange.data.Domain method)
has_discrete_attributes() (Orange.data.Domain method)
has_meta() (Orange.data.Instance method)
has_missing_classes() (Orange.data.Table method)
has_missing_values() (Orange.data.Table method)
has_other_attributes() (Orange.data.Domain method)
HasClassValue (class in Orange.data.filter)
HasMeta (class in Orange.data.filter)
height (Orange.clustering.hierarchical.HierarchicalCluster attribute)
HexagonalTopology (in module Orange.projection.som)
HierarchicalCluster (class in Orange.clustering.hierarchical)
HierarchicalClustering (class in Orange.clustering.hierarchical)
high (Orange.feature.discretization.BiModalDiscretizer attribute)
hSlider() (in module OWGUI)

I

id (Orange.data.filter.HasMeta attribute)
IgnoreUnknowns (Orange.feature.scoring.Score attribute)
importances() (Orange.ensemble.forest.ScoreFeature method)
imputation , []
Impute (class in Orange.data.preprocess)
impute_class (Orange.feature.imputation.Constructor attribute)
(Orange.feature.imputation.Random attribute)
impute_table() (Orange.regression.base.BaseRegressionLearner method)
ImputeClassifier (class in Orange.feature.imputation)
ImputeLearner (class in Orange.feature.imputation)
imputer (Orange.feature.imputation.ImputeClassifier attribute)
imputer_constructor (Orange.feature.imputation.ImputeLearner attribute)
include_same (Orange.classification.knn.FindNearestConstructor attribute)
increment (Orange.classification.tree.C45Learner attribute)
indentedBox() (in module OWGUI)
inertia_of_axes() (Orange.projection.correspondence.CA method)
Infinity (Orange.classification.logreg.LogRegFitter attribute)
info() (in module Orange.utils.serverfiles)
(Orange.utils.serverfiles.ServerFiles method)
InfoGain (class in Orange.feature.scoring)
init_centroids() (Orange.clustering.kmeans.Clustering method)
init_diversity() (Orange.clustering.kmeans static method)
init_hclustering (class in Orange.clustering.kmeans)
init_random() (Orange.clustering.kmeans static method)
initialize_map_linear() (Orange.projection.som.Map method)
initialize_map_random() (Orange.projection.som.Map method)
InitializeLinear (in module Orange.projection.som)
initializer (Orange.classification.rules.Orange.classification.rules.BeamFinder attribute)
InitializeRandom (in module Orange.projection.som)
initseed (Orange.misc.Random attribute)
innerDistribution (Orange.statistics.contingency.Table attribute)
innerDistributionUnknown (Orange.statistics.contingency.Table attribute)
innerVariable (Orange.statistics.contingency.Table attribute)
input_domain (Orange.projection.linear.Projector attribute)
insert_dot() (in module Orange.classification.tree)
insert_num() (in module Orange.classification.tree)
insert_str() (in module Orange.classification.tree)
Instance (class in Orange.data)
instance() (Orange.classification.tree.TreeLearner method)
(Orange.regression.tree.TreeLearner method)
instances (Orange.classification.knn.FindNearest attribute)
(Orange.classification.rules.Orange.classification.rules.Rule attribute)
(Orange.projection.som.Node attribute)
IntervalDiscretizer (class in Orange.feature.discretization)
inv_transform() (OrangeWidgets.plot.owplot.OWPlot method)
invert (Discrete2Continuous attribute)
invert() (Orange.misc.SymMatrix method)
IS() (in module Orange.evaluation.scoring)
is_DC() (Orange.data.Value method)
is_DK() (Orange.data.Value method)
is_in_background() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
is_marked() (OrangeWidgets.plot.owpoint.OWPoint method)
is_optional_meta() (Orange.data.Domain method)
is_selected() (OrangeWidgets.plot.owpoint.OWPoint method)
is_special() (Orange.data.Value method)
IsDefined (class in Orange.data.filter)
items (Orange.classification.tree.C45Node attribute)
items() (Orange.statistics.distribution.Distribution method)
iteration (Orange.clustering.kmeans.Clustering attribute)
iteration_number (Orange.evaluation.testing.TestedExample attribute)

J

joining_cluster() (in module Orange.clustering.hierarchical)

K

k (Orange.classification.knn.kNNClassifier attribute)
(Orange.classification.knn.kNNLearner attribute)
(Orange.clustering.kmeans.Clustering attribute)
(Orange.feature.scoring.Relief attribute)
(Orange.multilabel.brknn.BRkNNLearner attribute)
(Orange.multilabel.mlknn.MLkNNLearner attribute)
(Orange.multilabel.multiknn.MultikNNLearner attribute)
Kernel (class in Orange.statistics.estimate)
KernelWrapper (class in Orange.classification.svm.kernels)
keys() (Orange.statistics.distribution.Distribution method)
knn (Orange.multilabel.brknn.BRkNNLearner attribute)
(Orange.multilabel.mlknn.MLkNNLearner attribute)
(Orange.multilabel.multiknn.MultikNNLearner attribute)
kNNClassifier (class in Orange.classification.knn)
kNNLearner (class in Orange.classification.knn)

L

label() (in module OWGUI)
(OrangeWidgets.plot.owpoint.OWPoint method)
label_indices (Orange.multilabel.multiknn.MultikNNLearner attribute)
LabelPowerset Classifier
LabelPowerset Learner , []
LabelPowersetClassifier (class in Orange.multilabel)
LabelPowersetLearner (class in Orange.multilabel)
Laplace (class in Orange.statistics.estimate)
LaplaceEvaluator (class in Orange.classification.rules)
LassoRegression (class in Orange.regression.lasso)
LassoRegressionLearner (class in Orange.regression.lasso)
last (Orange.clustering.hierarchical.HierarchicalCluster attribute)
law (Orange.projection.linear.FreeViz attribute)
leaf (Orange.classification.tree.C45Node attribute)
learn_and_test_on_learn_data() (Orange.evaluation.testing.Evaluation method)
learn_and_test_on_test_data() (Orange.evaluation.testing.Evaluation method)
Learner (class in Orange.classification)
learner (Orange.classification.rules.Orange.classification.rules.Rule attribute)
(Orange.tuning.ThresholdLearner attribute)
(Orange.tuning.TuneParameters attribute)
learning_curve() (Orange.evaluation.testing.Evaluation method)
learning_curve_n() (Orange.evaluation.testing.Evaluation method)
learning_curve_with_test_data() (Orange.evaluation.testing.Evaluation method)
leave_one_out() (Orange.evaluation.testing.Evaluation method)
left (Orange.clustering.hierarchical.HierarchicalCluster attribute)
leverage (Orange.associate.AssociationRule attribute)
LibLinearLogRegLearner (class in Orange.classification.logreg)
lift (Orange.associate.AssociationRule attribute)
likelihood (Orange.classification.logreg.LogRegClassifier attribute)
LimitedCounter (class in Orange.utils.counters)
linear model
linear projection
LinearClassifier (class in Orange.classification.svm)
LinearRegression (class in Orange.regression.linear)
LinearRegressionLearner (class in Orange.regression.linear)
LinearSVMLearner (class in Orange.classification.svm)
lineEdit() (in module OWGUI)
linkage (Orange.clustering.hierarchical.HierarchicalClustering attribute)
listBox() (in module OWGUI)
listdomains() (in module Orange.utils.serverfiles)
(Orange.utils.serverfiles.ServerFiles method)
listfiles() (in module Orange.utils.serverfiles)
(Orange.utils.serverfiles.ServerFiles method)
localpath() (in module Orange.utils.serverfiles)
localpath_download() (in module Orange.utils.serverfiles)
Loess (class in Orange.statistics.estimate)
LogRegClassifier (class in Orange.classification.logreg)
LogRegFitter (class in Orange.classification.logreg)
LogRegFitter_Cholesky (class in Orange.classification.logreg)
LogRegLearner (class in Orange.classification.logreg)
lookup_from_data() (in module Orange.classification.lookup)
lookup_from_function() (in module Orange.classification.lookup)
lookup_table (Orange.classification.lookup.ClassifierByLookupTable attribute)
LookupLearner (class in Orange.classification.lookup)
low (Orange.feature.discretization.BiModalDiscretizer attribute)
lsmt() (Orange.projection.mds.MDS method)

M

M (class in Orange.statistics.estimate)
m (Orange.classification.bayes.NaiveLearner attribute)
(Orange.classification.tree.Pruner_m attribute)
(Orange.feature.scoring.MSE attribute)
(Orange.feature.scoring.Relief attribute)
(Orange.regression.linear.LinearRegression attribute)
m_pruning (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
MAE() (in module Orange.evaluation.scoring)
Mahalanobis (class in Orange.distance)
MahalanobisDistance (class in Orange.distance)
main_title (OrangeWidgets.plot.owplot.OWPlot attribute)
majority classifier
classification
MajorityLearner (class in Orange.classification.majority)
Manhattan (class in Orange.distance)
ManhattanDistance (class in Orange.distance)
Map (class in Orange.projection.som)
map (Orange.projection.som.Map attribute)
map_from_graph() (OrangeWidgets.plot.owplot.OWPlot method)
map_shape (Orange.projection.som.Map attribute)
map_to_graph() (OrangeWidgets.plot.owplot.OWPlot method)
MapIntValue (built-in class)
mapping (MapIntValue attribute)
(Orange.classification.tree.C45Node attribute)
(Orange.clustering.hierarchical.HierarchicalCluster attribute)
mark_points() (OrangeWidgets.plot.owplot.OWPlot method)
marked_points() (OrangeWidgets.plot.owplot.OWPlot method)
Marker (class in OrangeWidgets.plot.owtools)
matrix_type (Orange.misc.SymMatrix attribute)
max (Orange.data.filter.ValueFilterContinous attribute)
(Orange.data.filter.ValueFilterString attribute)
(Orange.statistics.basic.Variable attribute)
max_depth (Orange.classification.tree.SimpleTreeLearner attribute)
(Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
max_item_sets (Orange.associate.AssociationRulesInducer attribute)
(Orange.associate.AssociationRulesSparseInducer attribute)
max_majority (Orange.classification.tree.SimpleTreeLearner attribute)
(Orange.classification.tree.StopCriteria_common attribute)
(Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
max_nu() (Orange.classification.svm static method)
(Orange.classification.svm.SVMLearner static method)
Maximal (class in Orange.distance)
MaximalDistance (class in Orange.distance)
maybeTip() (OrangeWidgets.plot.owtools.TooltipManager method)
MCC() (in module Orange.evaluation.scoring)
McNemar() (in module Orange.evaluation.scoring)
McNemar_of_two() (in module Orange.evaluation.scoring)
MDL (class in Orange.feature.scoring)
MDS (class in Orange.projection.mds)
mean (Orange.statistics.distribution.Gaussian attribute)
measure (Orange.classification.tree.SplitConstructor_Score attribute)
(Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
menu_button() (OrangeWidgets.plot.OWPlotGUI method)
merge_data_sets() (Orange.data.preprocess.scaling.ScaleData method)
mergeDataSets() (Orange.data.preprocess.scaling.ScaleData method)
meta_attribute_load_status (Orange.data.Table attribute)
meta_id() (Orange.data.Domain method)
meta_names (Orange.data.sql.SQLReader attribute)
min (Orange.statistics.basic.Variable attribute)
min_instances (Orange.classification.tree.SimpleTreeLearner attribute)
(Orange.classification.tree.StopCriteria_common attribute)
(Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
min_objs (Orange.classification.tree.C45Learner attribute)
min_subset (Orange.classification.tree.SplitConstructor attribute)
(Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
mirror_symmetry (Orange.projection.linear.FreeViz attribute)
misc
selection
ML-kNN Classifier
ML-kNN Learner , []
mlc_accuracy() (in module Orange.evaluation.scoring)
mlc_hamming_loss() (in module Orange.evaluation.scoring)
mlc_precision() (in module Orange.evaluation.scoring)
mlc_recall() (in module Orange.evaluation.scoring)
MLkNNClassifier (class in Orange.multilabel)
MLkNNLearner (class in Orange.multilabel)
mode (Orange.regression.pls.PLSRegressionLearner attribute)
Model (class in Orange.feature.imputation)
model (Orange.regression.lasso.LassoRegression attribute)
ModelConstructor (class in Orange.feature.imputation)
models (Orange.feature.imputation.Model attribute)
modus() (Orange.statistics.distribution.Distribution method)
MofNCounter (class in Orange.utils.counters)
move_item() (in module OrangeWidgets.plot.owtools)
move_item_xy() (in module OrangeWidgets.plot.owtools)
MSE (class in Orange.feature.scoring)
MSE() (in module Orange.evaluation.scoring)
mu_x (Orange.regression.lasso.LassoRegression attribute)
mu_y (Orange.regression.linear.LinearRegression attribute)
MultiClassSVMLearner (class in Orange.classification.svm)
multidimensional scaling (mds)
MultikNN Classifier
MultikNN Learner , []
MultikNNClassifier (class in Orange.multilabel)
MultikNNLearner (class in Orange.multilabel)
multilabel
MultikNN Learner
multinomial_treatment (Orange.data.continuization.DomainContinuizer attribute)
MultiplicationKernelWrapper (class in Orange.classification.svm.kernels)

N

n (Orange.feature.discretization.EqualFreq attribute)
(Orange.feature.discretization.EqualWidth attribute)
(Orange.feature.discretization.EqualWidthDiscretizer attribute)
(Orange.projection.mds.MDS attribute)
(Orange.regression.linear.LinearRegression attribute)
(Orange.statistics.basic.Variable attribute)
n_comp (Orange.regression.pls.PLSRegressionLearner attribute)
n_examples (Orange.associate.AssociationRule attribute)
(Orange.classification.knn.kNNClassifier attribute)
naive Bayes classifier
Naive Bayesian Learner
NaiveClassifier (class in Orange.classification.bayes)
NaiveLearner (class in Orange.classification.bayes)
name (Orange.feature.Descriptor attribute)
(Orange.OrangeWidgets.plot.owcurve.OWCurve attribute)
native() (Orange.data.Instance method)
(Orange.data.Value method)
(Orange.statistics.distribution.Distribution method)
nearest_point() (OrangeWidgets.plot.owplot.OWPlot method)
needs (Orange.feature.scoring.Score attribute)
needs_update() (in module Orange.utils.serverfiles)
negate (Orange.data.filter.Filter attribute)
NeighbourhoodBubble (in module Orange.projection.som)
NeighbourhoodEpanechicov (in module Orange.projection.som)
NeighbourhoodGaussian (in module Orange.projection.som)
Neural Network Classifier
Neural Network Learner , []
NeuralNetworkClassifier (class in Orange.classification.neural)
NeuralNetworkLearner (class in Orange.classification.neural)
next() (Orange.utils.counters.BooleanCounter method)
(Orange.utils.counters.CanonicFuncCounter method)
(Orange.utils.counters.LimitedCounter method)
(Orange.utils.counters.MofNCounter method)
(Orange.utils.counters.NondecreasingCounter method)
nipals_xy() (in module Orange.regression.pls)
Node (class in Orange.classification.tree)
(class in Orange.projection.som)
node_classifier (Orange.classification.tree.Node attribute)
node_learner (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
node_type (Orange.classification.tree.C45Node attribute)
NondecreasingCounter (class in Orange.utils.counters)
normalize() (Orange.misc.SymMatrix method)
(Orange.statistics.contingency.Domain method)
(Orange.statistics.contingency.Table method)
(Orange.statistics.distribution.Distribution method)
normalize_continuous (Orange.data.continuization.DomainContinuizer attribute)
normalize_matrix() (in module Orange.regression.pls)
NormalizeContinuous (built-in class)
normalized (Orange.statistics.distribution.Distribution attribute)
normalizers (Orange.distance.DistanceNormalized attribute)
NPV() (in module Orange.evaluation.scoring)
num_labels (Orange.multilabel.multiknn.MultikNNLearner attribute)
number_of_decimals (Orange.feature.Continuous attribute)
number_of_iterations (Orange.evaluation.testing.ExperimentResults attribute)
number_of_learners (Orange.evaluation.testing.ExperimentResults attribute)

O

objects (Orange.clustering.hierarchical.HierarchicalCluster.mapping attribute)
OK (Orange.classification.logreg.LogRegFitter attribute)
one_fold_with_indices() (Orange.evaluation.testing.Evaluation method)
oper (Orange.data.filter.ValueFilterContinous attribute)
(Orange.data.filter.ValueFilterString attribute)
optimize_separation() (Orange.projection.linear.FreeViz method)
Orange.classification (module)
Orange.classification.bayes (module)
Orange.classification.knn (module)
Orange.classification.logreg (module)
Orange.classification.neural (module)
Orange.classification.rules.BeamFinder (class in Orange.classification.rules)
Orange.classification.rules.Evaluator (class in Orange.classification.rules)
Orange.classification.rules.Evaluator_Entropy (class in Orange.classification.rules)
Orange.classification.rules.Evaluator_Laplace (class in Orange.classification.rules)
Orange.classification.rules.Evaluator_LRS (class in Orange.classification.rules)
Orange.classification.rules.Evaluator_mEVC (class in Orange.classification.rules)
Orange.classification.rules.Finder (class in Orange.classification.rules)
Orange.classification.rules.Rule (class in Orange.classification.rules)
Orange.classification.rules.RuleLearner (class in Orange.classification.rules)
Orange.clustering.consensus (module)
Orange.clustering.hierarchical (module)
Orange.clustering.kmeans (module)
Orange.data.outliers (module)
Orange.data.preprocess (module)
Orange.data.preprocess.scaling (module)
Orange.data.sample (module)
Orange.ensemble (module)
Orange.evaluation.scoring (module)
Orange.evaluation.testing (module)
Orange.feature (module)
Orange.misc (module)
Orange.multilabel.br (module)
Orange.multilabel.brknn (module)
Orange.multilabel.lp (module)
Orange.multilabel.mlknn (module)
Orange.multilabel.multiknn (module)
Orange.OrangeWidgets.plot.owcurve (module)
Orange.projection.correspondence (module)
Orange.projection.linear (module)
Orange.projection.mds (module)
Orange.projection.som (module)
Orange.regression.base (module)
Orange.regression.lasso (module)
Orange.regression.linear (module)
Orange.regression.pls (module)
Orange.regression.tree (module)
Orange.statistics (module)
Orange.statistics.contingency (module)
Orange.statistics.estimate (module)
Orange.testing.testing (module)
Orange.tuning (module)
Orange.utils (module)
Orange.utils.addons (module)
Orange.utils.counters (module)
Orange.utils.environ (module)
Orange.utils.render (module)
Orange.utils.selection (module)
Orange.utils.serverfiles (module)
OrangeWidgets.plot.owlegend (module)
OrangeWidgets.plot.owplot (module)
OrangeWidgets.plot.owplotgui (module)
OrangeWidgets.plot.owpoint (module)
OrangeWidgets.plot.owtools (module)
order_leaves() (in module Orange.clustering.hierarchical)
OrderAttributes (class in Orange.feature.scoring)
ordered (Orange.feature.Descriptor attribute)
ordered_column_indices() (Orange.projection.correspondence.CA method)
ordered_row_indices() (Orange.projection.correspondence.CA method)
Ordinal2Continuous (built-in class)
OrientedWidget (class in OrangeWidgets.plot.owplotgui)
original_distances (Orange.projection.mds.MDS attribute)
outerDistribution (Orange.statistics.contingency.Table attribute)
outerVariable (Orange.statistics.contingency.Table attribute)
outlier
detection
outlier detection
OutlierDetection (class in Orange.data.outliers)
output_domain (Orange.projection.linear.Projector attribute)
overwrite_matrix (Orange.clustering.hierarchical.HierarchicalClustering attribute)
OWButton (class in OrangeWidgets.plot.owplotgui)
OWContexts (module)
OWCurve (class in Orange.OrangeWidgets.plot.owcurve)
OWGUI (module)
OWLegend (class in OrangeWidgets.plot.owlegend)
OWLegendItem (class in OrangeWidgets.plot.owlegend)
OWLegendTitle (class in OrangeWidgets.plot.owlegend)
OWMultiCurve (class in Orange.OrangeWidgets.plot.owcurve)
owner (Orange.data.Table attribute)
owns_instances (Orange.data.Table attribute)
OWPlot (class in OrangeWidgets.plot)
OWPlot.AddSelection (in module OrangeWidgets.plot.owplot)
OWPlot.RemoveSelection (in module OrangeWidgets.plot.owplot)
OWPlot.ReplaceSelection (in module OrangeWidgets.plot.owplot)
OWPlot.ToggleSelection (in module OrangeWidgets.plot.owplot)
OWPlotGUI (class in OrangeWidgets.plot)
OWPlotItem (class in Orange.OrangeWidgets.plot.owcurve)
OWPoint (class in OrangeWidgets.plot.owpoint)
OWToolbar (class in OrangeWidgets.plot.owplotgui)

P

P (Orange.classification.logreg.LogRegClassifier attribute)
p (Orange.data.sample.SubsetIndicesN attribute)
P (Orange.regression.pls.PLSRegression attribute)
p() (Orange.classification.bayes.NaiveClassifier method)
p0 (Orange.data.sample.SubsetIndices2 attribute)
p_attr() (Orange.statistics.contingency.ClassVar method) , []
(Orange.statistics.contingency.VarVar method) , []
p_class() (Orange.statistics.contingency.VarClass method) , []
p_vals (Orange.regression.lasso.LassoRegression attribute)
(Orange.regression.linear.LinearRegression attribute)
parameter (Orange.tuning.Tune1Parameter attribute)
parameters (Orange.tuning.TuneMParameters attribute)
PCA
(class in Orange.projection.linear)
PcaProjector (class in Orange.projection.linear)
PearsonR (class in Orange.distance)
PearsonRDistance (class in Orange.distance)
percentile() (Orange.statistics.distribution.Continuous method)
permute() (Orange.clustering.hierarchical.HierarchicalCluster method)
permute_responses() (in module Orange.regression.lasso)
plot
(module)
plot() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
plot_items() (OrangeWidgets.plot.owplot.OWPlot method)
plot_margin (OrangeWidgets.plot.owplot.OWPlot attribute)
plot_scree_diagram() (Orange.projection.correspondence.CA method)
plot_settings_box() (OrangeWidgets.plot.OWPlotGUI method)
plot_silhouette() (Orange.clustering.kmeans static method)
PLSRegression (class in Orange.regression.pls)
PLSRegressionLearner (class in Orange.regression.pls)
point_at() (OrangeWidgets.plot.owplot.OWPlot method)
point_item() (Orange.OrangeWidgets.plot.owcurve.OWCurve method)
point_properties_box() (OrangeWidgets.plot.OWPlotGUI method)
point_size_slider() (OrangeWidgets.plot.OWPlotGUI method)
points (Orange.feature.discretization.EqualWidthDiscretizer attribute)
(Orange.feature.discretization.IntervalDiscretizer attribute)
(Orange.projection.mds.MDS attribute)
polygon_from_data() (OrangeWidgets.plot.owtools.PolygonCurve static method)
PolygonCurve (class in OrangeWidgets.plot.owtools)
PolyKernelWrapper (class in Orange.classification.svm.kernels)
pos (Orange.projection.som.Node attribute)
position (ClassifierFromVarFD attribute)
(Orange.data.filter.SameValue attribute)
(Orange.data.filter.ValueFilter attribute)
postorder() (in module Orange.clustering.hierarchical)
PPV() (in module Orange.evaluation.scoring)
Precision() (in module Orange.evaluation.scoring)
preorder() (in module Orange.clustering.hierarchical)
PreprocessedLearner (class in Orange.tuning)
PreprocessorList (class in Orange.data.preprocess)
Pricipal Component Analysis
print_rules() (in module Orange.associate)
printline() (Orange.utils.ConsoleProgressBar method)
prob (Orange.data.filter.Random attribute)
prob_thresh (Orange.classification.tree.C45Learner attribute)
probabilities (Orange.evaluation.testing.TestedExample attribute)
(Orange.statistics.estimate.ConditionalEstimatorFromDistribution attribute)
(Orange.statistics.estimate.EstimatorFromDistribution attribute)
Probability Estimation
progress_callback (Orange.clustering.hierarchical.HierarchicalClustering attribute)
(Orange.projection.mds.MDS attribute)
progressBarFinished()
progressBarInit()
progressBarSet()
projected_distances (Orange.projection.mds.MDS attribute)
projection
linear
multidimensional scaling (mds)
self-organizing map (SOM)
projection (Orange.projection.linear.Projector attribute)
projection, Fisher Discriminant Analysis
projection, Principal Component Analysis
Projector (class in Orange.projection.linear)
proportion_test() (Orange.evaluation.testing.Evaluation method)
protect() (Orange.utils.serverfiles.ServerFiles method)
protection() (Orange.utils.serverfiles.ServerFiles method)
prune (Orange.classification.tree.C45Learner attribute)
prune() (in module Orange.clustering.hierarchical)
pruned() (in module Orange.clustering.hierarchical)
Pruner (class in Orange.classification.tree)
Pruner_m (class in Orange.classification.tree)
Pruner_SameMajority (class in Orange.classification.tree)
pruning
classification trees
purge() (Orange.statistics.basic.Domain method)
Python (class in Orange.feature)

Q

Q (Orange.regression.pls.PLSRegression attribute)
quality (Orange.classification.rules.Orange.classification.rules.Rule attribute)
query (Orange.data.sql.SQLReader attribute)

R

r2 (Orange.regression.linear.LinearRegression attribute)
R2() (in module Orange.evaluation.scoring)
r2adj (Orange.regression.linear.LinearRegression attribute)
radial_anchors() (Orange.projection.linear.FreeViz method)
radioButton() (in module OWGUI)
radioButtonsInBox() (in module OWGUI)
radius_seq() (Orange.projection.som.Solver method)
RAE() (in module Orange.evaluation.scoring)
Random (class in Orange.data.filter)
(class in Orange.feature.imputation)
(class in Orange.misc)
random forest
random() (Orange.statistics.distribution.Distribution method)
random_anchors() (Orange.projection.linear.FreeViz method)
random_generator (Orange.classification.tree.SimpleTreeLearner attribute)
(Orange.data.Table attribute)
(Orange.data.filter.Random attribute)
(Orange.data.sample.SubsetIndices attribute)
(Orange.feature.Descriptor attribute)
(Orange.statistics.distribution.Distribution attribute)
random_instance() (Orange.data.Table method)
RandomForestClassifier (class in Orange.ensemble.forest)
RandomForestLearner (class in Orange.ensemble.forest)
randomvalue() (Orange.feature.Descriptor method)
randseed (Orange.data.sample.SubsetIndices attribute)
rank_weight (Orange.classification.knn.kNNClassifier attribute)
(Orange.classification.knn.kNNLearner attribute)
RBFKernelWrapper (class in Orange.classification.svm.kernels)
Recall() (in module Orange.evaluation.scoring)
RectangleCurve (class in OrangeWidgets.plot.owtools)
RectangularTopology (in module Orange.projection.som)
ReduceByUnknown (Orange.feature.scoring.Score attribute)
reference_instance (Orange.projection.som.Node attribute)
refiner (Orange.classification.rules.Orange.classification.rules.BeamFinder attribute)
register_points() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
regression , [], [], [], []
linear
mean
tree , []
regression tree
RelativeFrequency (class in Orange.statistics.estimate)
Relevance (class in Orange.feature.scoring)
Relief (class in Orange.distance)
(class in Orange.feature.scoring) , []
ReliefDistance (class in Orange.distance)
remove() (in module Orange.utils.serverfiles)
(Orange.evaluation.testing.ExperimentResults method)
(Orange.utils.serverfiles.ServerFiles method)
remove_category() (OrangeWidgets.plot.owlegend.OWLegend method)
remove_domain() (in module Orange.utils.serverfiles)
(Orange.utils.serverfiles.ServerFiles method)
remove_duplicates() (Orange.data.Table method)
remove_meta() (Orange.data.Domain method)
(Orange.data.Instance method)
remove_meta_attribute() (Orange.data.Table method)
removeAll() (OrangeWidgets.plot.owtools.TooltipManager method)
RemoveContinuous (class in Orange.data.preprocess)
RemoveDiscrete (class in Orange.data.preprocess)
RemoveUnusedValues (class in Orange.data.preprocess)
repel_g (Orange.projection.linear.FreeViz attribute)
rescale_data() (Orange.data.preprocess.scaling.ScaleData method)
rescaleData() (Orange.data.preprocess.scaling.ScaleData method)
reset() (Orange.misc.Random method)
residuals (Orange.regression.linear.LinearRegression attribute)
resize_plot_item_list() (in module OrangeWidgets.plot.owtools)
results (Orange.evaluation.testing.ExperimentResults attribute)
return_what (Orange.tuning.TuneParameters attribute)
RFE (class in Orange.classification.svm)
(class in Orange.data.preprocess)
right (Orange.clustering.hierarchical.HierarchicalCluster attribute)
RMSE() (in module Orange.evaluation.scoring)
rnd_correction() (Orange.data.preprocess.scaling.ScaleData method)
rndCorrection() (Orange.data.preprocess.scaling.ScaleData method)
row_factors() (Orange.projection.correspondence.CA method)
row_inertia() (Orange.projection.correspondence.CA method)
row_principal_axes (Orange.projection.correspondence.CA attribute)
row_profiles() (Orange.projection.correspondence.CA method)
RRSE() (in module Orange.evaluation.scoring)
RSE() (in module Orange.evaluation.scoring)
rubber() (in module OWGUI)
rule induction
rule_filter (Orange.classification.rules.Orange.classification.rules.BeamFinder attribute)
rule_finder (Orange.classification.rules.Orange.classification.rules.RuleLearner attribute)
rule_stopping (Orange.classification.rules.Orange.classification.rules.RuleLearner attribute)
rule_to_string() (Orange.classification.rules static method)
RuleCovererAndRemover (class in Orange.classification.rules)
run() (Orange.clustering.kmeans.Clustering method)
(Orange.projection.mds.MDS method)
runone() (Orange.clustering.kmeans.Clustering method)

S

S2NHeuristicLearner (class in Orange.projection.linear)
same_majority_pruning (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
SameValue (class in Orange.data.filter)
Sample (class in Orange.data.preprocess)
Sampling
save_projection_as_tab_data() (Orange.data.preprocess.scaling.ScaleLinProjData method)
(Orange.data.preprocess.scaling.ScaleLinProjData3D method)
saveProjectionAsTabData() (Orange.data.preprocess.scaling.ScaleLinProjData method)
(Orange.data.preprocess.scaling.ScaleLinProjData3D method)
scale (Orange.projection.linear.Projector attribute)
scale_example_value() (Orange.data.preprocess.scaling.ScaleData method)
ScaleData (class in Orange.data.preprocess.scaling)
scaleExampleValue() (Orange.data.preprocess.scaling.ScaleData method)
ScaleLinProjData (class in Orange.data.preprocess.scaling)
ScaleLinProjData3D (class in Orange.data.preprocess.scaling)
ScalePolyvizData (class in Orange.data.preprocess.scaling)
ScaleScatterPlotData (class in Orange.data.preprocess.scaling)
scaling
scientific_format (Orange.feature.Continuous attribute)
Score (class in Orange.feature.scoring)
score (Orange.feature.scoring.OrderAttributes attribute)
score_all() (in module Orange.feature.scoring)
score_distance_to_centroids() (Orange.clustering.kmeans static method)
score_fast_silhouette() (Orange.clustering.kmeans static method)
score_silhouette() (Orange.clustering.kmeans static method)
ScoreFeature (class in Orange.ensemble.forest)
ScoreFromProbabilities (class in Orange.feature.scoring)
ScoreSVMWeights (class in Orange.classification.svm)
scoring (Orange.clustering.kmeans.Clustering attribute)
scree_plot() (Orange.projection.linear.PcaProjector method)
search() (in module Orange.utils.serverfiles)
(Orange.utils.serverfiles.ServerFiles method)
select() (Orange.data.Table method)
(Orange.feature.selection static method)
select_above_threshold() (Orange.feature.selection static method)
select_best() (in module Orange.utils.selection)
select_best_index() (in module Orange.utils.selection)
select_points() (OrangeWidgets.plot.owplot.OWPlot method)
select_ref() (Orange.data.Table method)
select_relief() (Orange.feature.selection static method)
selected_points() (OrangeWidgets.plot.owplot.OWPlot method) , []
selection
selectNRandom() (in module Orange.data.preprocess)
selectPRandom() (in module Orange.data.preprocess)
self-organizing map (SOM)
Sensitivity() (in module Orange.evaluation.scoring)
separator() (in module OWGUI)
server files
ServerFiles (class in Orange.utils.serverfiles)
set_axes() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
set_axis_enabled() (OrangeWidgets.plot.owplot.OWPlot method)
set_axis_labels() (OrangeWidgets.plot.owplot.OWPlot method)
set_axis_scale() (OrangeWidgets.plot.owplot.OWPlot method)
set_class() (Orange.data.Instance method)
set_classes() (Orange.data.Instance method)
set_color() (OrangeWidgets.plot.owpoint.OWPoint method)
set_continuizer() (Orange.regression.base.BaseRegressionLearner method)
set_data() (Orange.OrangeWidgets.plot.owcurve.OWCurve method)
set_data_rect() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
set_distance_matrix() (Orange.data.outliers.OutlierDetection method)
set_examples() (Orange.data.outliers.OutlierDetection method)
set_floating() (OrangeWidgets.plot.owlegend.OWLegend method)
set_graph_transform() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
set_imputer() (Orange.regression.base.BaseRegressionLearner method)
set_in_background() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
set_knn() (Orange.data.outliers.OutlierDetection method)
set_label() (OrangeWidgets.plot.owpoint.OWPoint method)
set_main_curve_data() (OrangeWidgets.plot.owplot.OWPlot method)
set_main_title() (OrangeWidgets.plot.owplot.OWPlot method)
set_marked() (OrangeWidgets.plot.owpoint.OWPoint method)
set_orientation() (OrangeWidgets.plot.owlegend.OWLegend method)
set_point_colors() (Orange.OrangeWidgets.plot.owcurve.OWMultiCurve method)
set_point_sizes() (Orange.OrangeWidgets.plot.owcurve.OWMultiCurve method)
set_point_symbols() (Orange.OrangeWidgets.plot.owcurve.OWMultiCurve method)
set_result() (Orange.evaluation.testing.TestedExample method)
set_selected() (OrangeWidgets.plot.owpoint.OWPoint method)
set_show_main_title() (OrangeWidgets.plot.owplot.OWPlot method)
set_size() (OrangeWidgets.plot.owpoint.OWPoint method)
set_state() (Orange.utils.ConsoleProgressBar method)
set_style() (Orange.OrangeWidgets.plot.owcurve.OWCurve method)
set_symbol() (OrangeWidgets.plot.owpoint.OWPoint method)
set_weight() (Orange.data.Instance method)
set_zoom_transform() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
setcost() (Orange.misc.CostMatrix method)
setStopper() (in module OWGUI)
show_legend (OrangeWidgets.plot.owplot.OWPlot attribute)
show_legend_check_box() (OrangeWidgets.plot.OWPlotGUI method)
show_main_title (OrangeWidgets.plot.owplot.OWPlot attribute)
shuffle() (Orange.data.Table method)
sigma (Orange.statistics.distribution.Gaussian attribute)
SimpleTreeLearner (class in Orange.classification.tree)
SINGLE (in module Orange.clustering.hierarchical)
Singularity (Orange.classification.logreg.LogRegFitter attribute)
size() (OrangeWidgets.plot.owpoint.OWPoint method)
skip_prob (Orange.classification.tree.SimpleTreeLearner attribute)
smacof_step() (Orange.projection.mds.MDS method)
smooth (Orange.multilabel.mlknn.MLkNNLearner attribute)
Solver (class in Orange.projection.som)
SOMLearner (class in Orange.projection.som)
SOMMap (class in Orange.projection.som)
SOMSupervisedLearner (class in Orange.projection.som)
sort() (in module Orange.associate)
(Orange.data.Table method)
sorted_examples (Orange.classification.lookup.ClassifierByDataTable attribute)
span (NormalizeContinuous attribute)
SparseLinKernel (class in Orange.classification.svm.kernels)
SpearmanR (class in Orange.distance)
SpearmanRDistance (class in Orange.distance)
Specificity() (in module Orange.evaluation.scoring)
spin() (in module OWGUI)
split (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
split_by_iterations() (in module Orange.evaluation.scoring)
split_in_two (Orange.feature.discretization.BiModal attribute)
SplitConstructor (class in Orange.classification.tree)
SplitConstructor_Combined (class in Orange.classification.tree)
SplitConstructor_ExhaustiveBinary (class in Orange.classification.tree)
SplitConstructor_Feature (class in Orange.classification.tree)
SplitConstructor_OneAgainstOthers (class in Orange.classification.tree)
SplitConstructor_Score (class in Orange.classification.tree)
SplitConstructor_Threshold (class in Orange.classification.tree)
Splitter (class in Orange.classification.tree)
splitter (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
Splitter_IgnoreUnknowns (class in Orange.classification.tree)
Splitter_UnknownsAsBranchSizes (class in Orange.classification.tree)
Splitter_UnknownsAsSelector (class in Orange.classification.tree)
Splitter_UnknownsToAll (class in Orange.classification.tree)
Splitter_UnknownsToBranch (class in Orange.classification.tree)
Splitter_UnknownsToCommon (class in Orange.classification.tree)
Splitter_UnknownsToRandom (class in Orange.classification.tree)
SQLReader (class in Orange.data.sql)
SQLWriter (class in Orange.data.sql)
StackedClassificationLearner (class in Orange.ensemble.stacking)
StackedClassifier (class in Orange.ensemble.stacking)
stacking
standardize (Orange.projection.linear.Projector attribute)
state (Orange.utils.counters.BooleanCounter attribute)
(Orange.utils.counters.CanonicFuncCounter attribute)
(Orange.utils.counters.LimitedCounter attribute)
(Orange.utils.counters.MofNCounter attribute)
(Orange.utils.counters.NondecreasingCounter attribute)
state_buttons() (OrangeWidgets.plot.OWPlotGUI method)
StateButtonContainer (class in OrangeWidgets.plot.owplotgui)
std_coefficients (Orange.regression.linear.LinearRegression attribute)
std_error (Orange.regression.linear.LinearRegression attribute)
std_errors (Orange.regression.lasso.LassoRegression attribute)
step (Orange.feature.discretization.EqualWidthDiscretizer attribute)
stepwise() (in module Orange.regression.linear)
StepWiseFSS (class in Orange.classification.logreg)
stop (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
StopCriteria (class in Orange.classification.tree)
StopCriteria_common (class in Orange.classification.tree)
store_contingencies (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
store_curve (Orange.tuning.ThresholdLearner attribute)
store_distributions (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
store_examples (Orange.associate.AssociationRulesInducer attribute)
(Orange.associate.AssociationRulesSparseInducer attribute)
store_instances (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
store_node_classifier (Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
stratified (Orange.data.sample.SubsetIndices attribute)
strength (Orange.associate.AssociationRule attribute)
stress (Orange.projection.mds.MDS attribute)
String (class in Orange.feature)
style() (Orange.OrangeWidgets.plot.owcurve.OWCurve method)
subgroup discovery
subset (Orange.classification.tree.C45Learner attribute)
SubsetIndices (class in Orange.data.sample)
SubsetIndices.NotStratified (in module Orange.data.sample)
SubsetIndices.Stratified (in module Orange.data.sample)
SubsetIndices.StratifiedIfPossible (in module Orange.data.sample)
SubsetIndices2 (class in Orange.data.sample)
SubsetIndicesCV (class in Orange.data.sample)
SubsetIndicesN (class in Orange.data.sample)
subtransformer (TransformValue attribute)
sum (Orange.statistics.basic.Variable attribute)
sum2 (Orange.statistics.basic.Variable attribute)
support (Orange.associate.AssociationRule attribute)
(Orange.associate.AssociationRulesInducer attribute)
(Orange.associate.AssociationRulesSparseInducer attribute)
support vector machines (SVM)
supports_continuous (Orange.statistics.estimate.Estimator attribute)
supports_discrete (Orange.statistics.estimate.Estimator attribute)
svalue (Orange.data.Value attribute)
svd_xy() (in module Orange.regression.pls)
SVMLearner (class in Orange.classification.svm)
SVMLearnerEasy (class in Orange.classification.svm)
SVMLearnerSparse (class in Orange.classification.svm)
swap() (Orange.clustering.hierarchical.HierarchicalCluster method)
symbol() (OrangeWidgets.plot.owpoint.OWPoint method)
SymMatrix (class in Orange.misc)

T

T (Orange.regression.pls.PLSRegression attribute)
t_scores (Orange.regression.linear.LinearRegression attribute)
table
value imputation
Table (class in Orange.data)
(class in Orange.statistics.contingency)
table_to_svm_format() (Orange.classification.svm static method)
test_on_data() (Orange.evaluation.testing.Evaluation method)
test_with_indices() (Orange.evaluation.testing.Evaluation method)
tested (Orange.classification.tree.C45Node attribute)
TestedExample (class in Orange.evaluation.testing)
Testing
theme_name (OrangeWidgets.plot.owplot.OWPlot attribute)
threshold (Orange.feature.discretization.ThresholdDiscretizer attribute)
(Orange.tuning.ThresholdClassifier attribute)
threshold_function() (Orange.feature.scoring.Score method)
ThresholdClassifier (class in Orange.tuning)
ThresholdDiscretizer (class in Orange.feature.discretization)
ThresholdLearner (class in Orange.tuning)
title_margin (OrangeWidgets.plot.owplot.OWPlot attribute)
to_numpy() (Orange.data.Table method)
to_numpyMA() (Orange.data.Table method)
to_string() (Orange.classification.tree.C45Classifier method)
(Orange.classification.tree.TreeClassifier method)
(Orange.regression.lasso.LassoRegression method)
(Orange.regression.linear.LinearRegression method)
(Orange.regression.pls.PLSRegression method)
(Orange.regression.tree.TreeClassifier method)
tool_button() (OrangeWidgets.plot.OWPlotGUI method)
toolbar() (OrangeWidgets.plot.OWPlotGUI method)
TooltipManager (class in OrangeWidgets.plot.owtools)
top_cluster_membership() (in module Orange.clustering.hierarchical)
top_clusters() (in module Orange.clustering.hierarchical)
top_rated() (Orange.feature.selection static method)
topology (Orange.projection.som.Map attribute)
torgerson() (Orange.projection.mds.MDS method)
train_batch() (Orange.projection.som.Solver method)
train_sequential() (Orange.projection.som.Solver method)
train_step_batch() (Orange.projection.som.Solver method)
train_step_sequential() (Orange.projection.som.Solver method)
transform() (OrangeWidgets.plot.owplot.OWPlot method)
transform_unknowns (ClassifierFromVar attribute)
(ClassifierFromVarFD attribute)
transformer (ClassifierFromVar attribute)
(ClassifierFromVarFD attribute)
TransformValue (built-in class)
translate() (Orange.data.Table method) , []
tree (Orange.classification.tree.C45Classifier attribute)
(Orange.classification.tree.TreeClassifier attribute)
(Orange.regression.tree.TreeClassifier attribute)
tree_size() (Orange.classification.tree.Node method)
TreeClassifier (class in Orange.classification.tree)
(class in Orange.regression.tree)
TreeLearner (class in Orange.classification.tree)
(class in Orange.regression.tree)
trials (Orange.classification.tree.C45Learner attribute)
Tune1Parameter (class in Orange.tuning)
tune_parameters() (Orange.classification.svm.SVMLearner method)
TuneMParameters (class in Orange.tuning)
TuneParameters (class in Orange.tuning)
tuning

U

U (Orange.regression.pls.PLSRegression attribute)
UnconnectedLinesCurve (class in OrangeWidgets.plot.owtools)
unit_coords() (Orange.projection.som.Map method)
unit_distances() (Orange.projection.som.Map method)
unknowns (Orange.statistics.distribution.Distribution attribute)
unknowns_treatment (Orange.feature.scoring.MSE attribute)
(Orange.feature.scoring.Score attribute)
UnknownsAsValue (Orange.feature.scoring.Score attribute)
UnknownsToCommon (Orange.feature.scoring.Score attribute)
unmark_all_points() (OrangeWidgets.plot.owplot.OWPlot method)
unordered CN2
unprotect() (Orange.utils.serverfiles.ServerFiles method)
unselect_all_points() (OrangeWidgets.plot.owplot.OWPlot method)
update() (in module Orange.utils.serverfiles)
(Orange.data.sql.SQLReader method)
update_items() (OrangeWidgets.plot.owlegend.OWLegend method)
update_number_of_items() (Orange.OrangeWidgets.plot.owcurve.OWCurve method)
update_point_coordinates() (Orange.OrangeWidgets.plot.owcurve.OWCurve method)
update_point_positions() (Orange.OrangeWidgets.plot.owcurve.OWCurve method)
update_properties() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)
update_theme() (OrangeWidgets.plot.owplot.OWPlot method)
upload() (Orange.utils.serverfiles.ServerFiles method)
use_class (Orange.feature.imputation.ModelConstructor attribute)
uses (Orange.misc.Random attribute)
utils , [], []
counters
render

V

Value (class in Orange.data)
value (Discrete2Continuous attribute)
(Orange.data.Value attribute)
(Orange.data.filter.SameValue attribute)
value_type (Orange.data.Value attribute)
ValueFilter (class in Orange.data.filter)
ValueFilterContinous (class in Orange.data.filter)
ValueFilterDiscrete (class in Orange.data.filter)
ValueFilterString (class in Orange.data.filter)
ValueFilterStringList (class in Orange.data.filter)
Values (class in Orange.data.filter)
values (Orange.data.filter.ValueFilterDiscrete attribute)
(Orange.data.filter.ValueFilterStringList attribute)
(Orange.feature.Discrete attribute)
(Orange.tuning.Tune1Parameter attribute)
values() (Orange.statistics.distribution.Distribution method)
var() (Orange.statistics.distribution.Continuous method)
(Orange.statistics.distribution.Gaussian method)
var_type (Orange.data.Value attribute)
(Orange.feature.Descriptor attribute)
VarClass (class in Orange.statistics.contingency)
Variable (class in Orange.statistics.basic)
variable (Orange.data.Value attribute)
(Orange.statistics.basic.Variable attribute)
(Orange.statistics.contingency.Class attribute)
(Orange.statistics.distribution.Distribution attribute)
variables (Orange.classification.lookup.ClassifierByDataTable attribute)
(Orange.classification.lookup.ClassifierByLookupTable attribute)
(Orange.data.Domain attribute)
variance_sum (Orange.projection.linear.PcaProjector attribute)
variances (Orange.projection.linear.PcaProjector attribute)
varType (Orange.statistics.contingency.Table attribute)
VarVar (class in Orange.statistics.contingency)
VarVar() (Orange.statistics.contingency.VarVar method)
vectors() (Orange.projection.som.Map method)
verbose (Orange.tuning.TuneParameters attribute)
version (Orange.data.Domain attribute)
(Orange.data.Table attribute)

W

W (Orange.regression.pls.PLSRegression attribute)
wald_Z (Orange.classification.logreg.LogRegClassifier attribute)
WARD (in module Orange.clustering.hierarchical)
weight_ID (Orange.classification.knn.FindNearest attribute)
weight_id (Orange.classification.knn.kNNClassifier attribute)
(Orange.classification.knn.kNNLearner attribute)
(Orange.classification.rules.Orange.classification.rules.Rule attribute)
(Orange.tuning.TuneParameters attribute)
weights (Orange.classification.svm.LinearClassifier attribute)
(Orange.evaluation.testing.ExperimentResults attribute)
which_var (ClassifierFromVar attribute)
widgetBox() (in module OWGUI)
widgetLabel() (in module OWGUI)
window (Orange.classification.tree.C45Learner attribute)
worst_acceptable (Orange.classification.tree.SplitConstructor_Score attribute)
(Orange.classification.tree.TreeLearner attribute)
(Orange.regression.tree.TreeLearner attribute)
WRACCEvaluator (class in Orange.classification.rules)
write() (Orange.data.sql.SQLWriter method)

X

x_vars (Orange.regression.pls.PLSRegression attribute)

Y

y_vars (Orange.regression.pls.PLSRegression attribute)

Z

z_values() (Orange.data.outliers.OutlierDetection method)
zero_based (Discrete2Continuous attribute)
(Orange.data.continuization.DomainContinuizer attribute)
zoom_transform() (Orange.OrangeWidgets.plot.owcurve.OWPlotItem method)