26f677b05413ec78fbcd82445fe83dc5aac35f10,pyemma/coordinates/api.py,,cluster_mini_batch_kmeans,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,1338
Before Change
from pyemma.coordinates.clustering.kmeans import MiniBatchKmeansClustering
res = MiniBatchKmeansClustering(n_clusters=k, max_iter=max_iter, metric=metric, init_strategy=init_strategy,
batch_size=batch_size, n_jobs=n_jobs, skip=skip, clustercenters=clustercenters)
return _param_stage(data, res, chunk_size=chunk_size)
def cluster_kmeans(data=None, k=None, max_iter=10, tolerance=1e-5, stride=1,
metric="euclidean", init_strategy="kmeans++", fixed_seed=False,After Change
from pyemma.coordinates.clustering.kmeans import MiniBatchKmeansClustering
res = MiniBatchKmeansClustering(n_clusters=k, max_iter=max_iter, metric=metric, init_strategy=init_strategy,
batch_size=batch_size, n_jobs=n_jobs, skip=skip, clustercenters=clustercenters)
if data is not None:
res.estimate(data, chunksize=chunk_size)
return res
def cluster_kmeans(data=None, k=None, max_iter=10, tolerance=1e-5, stride=1,
metric="euclidean", init_strategy="kmeans++", fixed_seed=False,In pattern: SUPERPATTERN
Frequency: 4
Non-data size: 6
Instances Project Name: markovmodel/PyEMMA
Commit Name: 26f677b05413ec78fbcd82445fe83dc5aac35f10
Time: 2017-11-29
Author: m.scherer@fu-berlin.de
File Name: pyemma/coordinates/api.py
Class Name:
Method Name: cluster_mini_batch_kmeans
Project Name: markovmodel/PyEMMA
Commit Name: 26f677b05413ec78fbcd82445fe83dc5aac35f10
Time: 2017-11-29
Author: m.scherer@fu-berlin.de
File Name: pyemma/coordinates/api.py
Class Name:
Method Name: cluster_kmeans
Project Name: markovmodel/PyEMMA
Commit Name: 26f677b05413ec78fbcd82445fe83dc5aac35f10
Time: 2017-11-29
Author: m.scherer@fu-berlin.de
File Name: pyemma/coordinates/api.py
Class Name:
Method Name: cluster_uniform_time
Project Name: markovmodel/PyEMMA
Commit Name: 26f677b05413ec78fbcd82445fe83dc5aac35f10
Time: 2017-11-29
Author: m.scherer@fu-berlin.de
File Name: pyemma/coordinates/api.py
Class Name:
Method Name: cluster_regspace
