actableai.clustering package

Subpackages

• actableai.clustering.models package
  • Subpackages
    • actableai.clustering.models.tests package
      • Submodules
      • actableai.clustering.models.tests.test_models module
      • Module contents
  • Submodules
  • actableai.clustering.models.affinity_propagation module
  • actableai.clustering.models.agglomerative_clustering module
  • actableai.clustering.models.base module
  • actableai.clustering.models.dbscan module
  • actableai.clustering.models.dec module
  • actableai.clustering.models.kmeans module
  • actableai.clustering.models.spectral_clustering module
  • Module contents
• actableai.clustering.tests package
  • Submodules
  • actableai.clustering.tests.test_init module
  • Module contents

Submodules

actableai.clustering.config module

actableai.clustering.explain module

actableai.clustering.explain.generate_cluster_descriptions(tree, features, dummy_columns=None, min_precision=0.8)

actableai.clustering.metrics module

actableai.clustering.metrics.acc(y_true, y_pred)

Calculate clustering accuracy. Require scikit-learn installed

# Arguments

y: true labels, numpy.array with shape (n_samples,) y_pred: predicted labels, numpy.array with shape (n_samples,)

# Return

accuracy, in [0,1]

actableai.clustering.transform module

class actableai.clustering.transform.ClusteringDataTransformer(drop_low_info=True, drop_categorical=False)

Bases: sklearn.base.TransformerMixin, sklearn.base.BaseEstimator

Transform numeric columns using StandardScaler and categorical columns using OneHotEncoder.

fit_transform(X: pandas.core.frame.DataFrame)

Fit to data, then transform it.

Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.

Parameters

• X (array-like of shape (n_samples, n_features)) – Input samples.
• y (array-like of shape (n_samples,) or (n_samples, n_outputs), default=None) – Target values (None for unsupervised transformations).
• **fit_params (dict) – Additional fit parameters.

Returns

X_new – Transformed array.

Return type

ndarray array of shape (n_samples, n_features_new)

inverse_transform(X)

transform(X: pandas.core.frame.DataFrame)

class actableai.clustering.transform.ImputeAndStandardScaler

Bases: sklearn.pipeline.Pipeline

steps: List[Any]

Module contents