Scikit-Learn externals¶

Clustering¶

This is used to implement clustering algorithms not included in `scikit-learn`

class sekupy.ext.sklearn.cluster.PeakDensityClustering(dc='percentage', percentage=2.0, cluster_threshold=12.0, rhofx=<function gaussian_kernel>)[source]¶

fit(X, y=None)[source]¶

[summary]

Parameters:

X ([type]) – [description]
y ([type], optional) – [description], by default None

Returns:

[description]

Return type:

[type]

sekupy.ext.sklearn.cluster.cutoff(dist, dc)[source]¶

[summary]

Parameters:

dist ([type]) – [description]
dc ([type]) – [description]

Returns:

[description]

Return type:

[type]

sekupy.ext.sklearn.cluster.gaussian_kernel(dist, dc)[source]¶

[summary]

Parameters:

dist ([type]) – [description]
dc ([type]) – [description]

Returns:

[description]

Return type:

[type]

Feature Selection¶

sekupy.ext.sklearn.feature_selection.negative_correlated(X, y)[source]¶

[summary]

Parameters:

X ([type]) – [description]
y ([type]) – [description]

Returns:

[description]

Return type:

[type]

sekupy.ext.sklearn.feature_selection.pearsonr_score(X, y)[source]¶

sekupy.ext.sklearn.feature_selection.positive_correlated(X, y)[source]¶

[summary]

Parameters:

X ([type]) – [description]
y ([type]) – [description]

Returns:

[description]

Return type:

[type]