Changeset 10716:5d1600100484 in orange


Ignore:
Timestamp:
04/03/12 10:49:23 (2 years ago)
Author:
anze <anze.staric@…>
Branch:
default
Message:

Fixed failing tests.

Location:
docs/reference/rst/code
Files:
4 edited

Legend:

Unmodified
Added
Removed
  • docs/reference/rst/code/optimization-thresholding1.py

    r9823 r10716  
    44 
    55learner = Orange.classification.bayes.NaiveLearner() 
    6 thresh = Orange.optimization.ThresholdLearner(learner=learner) 
    7 thresh80 = Orange.optimization.ThresholdLearner_fixed(learner=learner,  
     6thresh = Orange.tuning.ThresholdLearner(learner=learner) 
     7thresh80 = Orange.tuning.ThresholdLearner_fixed(learner=learner, 
    88                                                      threshold=0.8) 
    99res = Orange.evaluation.testing.cross_validation([learner, thresh, thresh80], bupa) 
  • docs/reference/rst/code/optimization-thresholding2.py

    r9946 r10716  
    99 
    1010thresholds = [.2, .5, .8] 
    11 models = [Orange.optimization.ThresholdClassifier(bayes, thr) for thr in thresholds] 
     11models = [Orange.tuning.ThresholdClassifier(bayes, thr) for thr in thresholds] 
    1212 
    1313res = Orange.evaluation.testing.test_on_data(models, test) 
  • docs/reference/rst/code/optimization-tuning1.py

    r10634 r10716  
    33learner = Orange.classification.tree.TreeLearner() 
    44voting = Orange.data.Table("voting") 
    5 tuner = Orange.optimization.Tune1Parameter(learner=learner, 
     5tuner = Orange.tuning.Tune1Parameter(learner=learner, 
    66                           parameter="min_subset", 
    77                           values=[1, 2, 3, 4, 5, 10, 15, 20], 
     
    2020learner = Orange.classification.tree.TreeLearner(min_subset=10).instance() 
    2121voting = Orange.data.Table("voting") 
    22 tuner = Orange.optimization.Tune1Parameter(learner=learner, 
     22tuner = Orange.tuning.Tune1Parameter(learner=learner, 
    2323                    parameter=["split.continuous_split_constructor.min_subset", 
    2424                               "split.discrete_split_constructor.min_subset"], 
  • docs/reference/rst/code/optimization-tuningm.py

    r10077 r10716  
    33learner = Orange.classification.tree.TreeLearner() 
    44voting = Orange.data.Table("voting") 
    5 tuner = Orange.optimization.TuneMParameters(learner=learner, 
     5tuner = Orange.tuning.TuneMParameters(learner=learner, 
    66             parameters=[("min_subset", [2, 5, 10, 20]), 
    77                         ("measure", [Orange.feature.scoring.GainRatio(),  
Note: See TracChangeset for help on using the changeset viewer.