source: orange/orange/orngClustering.py @ 8059:f294534915ee

Revision 8059:f294534915ee, 3.1 KB checked in by markotoplak, 3 years ago (diff)

Moved Orange.distances into Orange.distance.instances.

Line 
1from Orange.clustering.kmeans import * 
2# from Orange.cluster.hierarchical import *
3
4from Orange.distance.instances import \
5     AlignmentList, \
6     DistanceMap, \
7     DistanceMapConstructor, \
8     ExampleDistConstructor, \
9     ExampleDistBySorting, \
10     ExampleDistVector, \
11     ExamplesDistance, \
12     ExamplesDistance_Normalized, \
13     ExamplesDistanceConstructor
14
15from Orange.distance.instances import Hamming as ExamplesDistance_Hamming
16from Orange.distance.instances import DTW as ExamplesDistance_DTW
17from Orange.distance.instances import Euclidean as ExamplesDistance_Euclidean
18from Orange.distance.instances import Manhattan as ExamplesDistance_Manhattan
19from Orange.distance.instances import Maximal as ExamplesDistance_Maximal
20from Orange.distance.instances import Relief as ExamplesDistance_Relief
21
22from Orange.distance.instances import DTWConstructor as ExamplesDistanceConstructor_DTW
23from Orange.distance.instances import EuclideanConstructor as ExamplesDistanceConstructor_Euclidean
24from Orange.distance.instances import HammingConstructor as ExamplesDistanceConstructor_Hamming
25from Orange.distance.instances import ManhattanConstructor as ExamplesDistanceConstructor_Manhattan
26from Orange.distance.instances import MaximalConstructor as ExamplesDistanceConstructor_Maximal
27from Orange.distance.instances import ReliefConstructor as ExamplesDistanceConstructor_Relief
28
29from Orange.distance.instances import PearsonRConstructor as ExamplesDistanceConstructor_PearsonR
30from Orange.distance.instances import PearsonR as ExamplesDistance_PearsonR
31from Orange.distance.instances import SpearmanRConstructor as ExamplesDistanceConstructor_SpearmanR
32from Orange.distance.instances import SpearmanR as ExamplesDistance_SpearmanR
33
34
35from Orange.clustering.kmeans import Clustering as KMeans
36from Orange.clustering.kmeans import init_random as kmeans_init_random
37from Orange.clustering.kmeans import init_diversity as kmeans_init_diversity
38from Orange.clustering.kmeans import init_hclustering as KMeans_init_hierarchicalClustering
39from Orange.clustering.kmeans import data_center as data_center
40from Orange.clustering.kmeans import plot_silhouette as plot_silhouette
41from Orange.clustering.kmeans import score_distance_to_centroids as score_distance_to_centroids
42from Orange.clustering.kmeans import score_silhouette as score_silhouette
43from Orange.clustering.kmeans import score_fast_silhouette as score_fastsilhouette
44
45from Orange.clustering.hierarchical import clustering as hierarchicalClustering
46from Orange.clustering.hierarchical import clustering_features as hierarchicalClustering_attributes
47from Orange.clustering.hierarchical import cluster_to_list as hierarchicalClustering_clusterList
48from Orange.clustering.hierarchical import top_clusters as hierarchicalClustering_topClusters
49from Orange.clustering.hierarchical import top_cluster_membership as hierarhicalClustering_topClustersMembership
50from Orange.clustering.hierarchical import order_leaves as orderLeaves
51
52from Orange.clustering.hierarchical import dendrogram_draw, DendrogramPlotPylab, DendrogramPlot
53#left for backward compatibility
54hierarchicalClustering_attributes
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