f78f4d1eb72309c8046b1469e30a7174fa115eed,examples/plot_kmeans_poincare_disk.py,,main,#,20

Before Change



    //labels = kmeans.predict(X=merged_clusters)

    centroids = gs.array([[0,0] ,[0.5,0.5]])

    visualization.plot(
            centroids,
            ax=ax,

After Change


                              init="random",
                              )

    centroids = kmeans.fit(X=merged_clusters, max_iter=1)

    //labels = kmeans.predict(X=merged_clusters)

    //centroids = gs.array([[0,0] ,[0.5,0.5]])
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 6

Instances


Project Name: geomstats/geomstats
Commit Name: f78f4d1eb72309c8046b1469e30a7174fa115eed
Time: 2020-01-23
Author: hadizaatiti@gmail.com
File Name: examples/plot_kmeans_poincare_disk.py
Class Name:
Method Name: main


Project Name: nipy/dipy
Commit Name: f6c10c53a483ff323359d5a6d7a1c54bd65e2753
Time: 2016-08-29
Author: rafaelnh21@gmail.com
File Name: dipy/reconst/tests/test_fwdti.py
Class Name:
Method Name: test_fwdti_predictions


Project Name: geomstats/geomstats
Commit Name: 5da96bc305e17265caf31e9c8216f66e804d456f
Time: 2020-01-23
Author: hadizaatiti@gmail.com
File Name: examples/plot_kmeans_poincare_disk.py
Class Name:
Method Name: main