Base Classes and Mixins¶
FSFC uses some base classes and mixins, based on sklearn
estimators and classifiers. It makes the library
fully compatible with sklearn
, so feature selectors can be used in pipelines
Mixins¶
Some default mixins which extend ones defined in sklearn

class
fsfc.mixins.
KBestSelectorMixin
[source]¶ Bases:
fsfc.mixins.ScoreSelectorMixin
Mixin that selects K best features according to their scores

class
fsfc.mixins.
ScoreSelectorMixin
[source]¶ Bases:
object
Mixin that adds getter for calculation of scores of features and checks that scores are calculated

class
fsfc.mixins.
ThresholdSelectorMixin
[source]¶ Bases:
fsfc.mixins.ScoreSelectorMixin
Mixin that selects features according to some threshold. That means that all features whose score is higher than threshold are selected
Classes¶
Base classes of all feature selecting / clustering algorithms of FSFC

class
fsfc.base.
BaseFeatureSelector
[source]¶ Bases:
sklearn.base.BaseEstimator
,sklearn.feature_selection.base.SelectorMixin
Base class for all feature selection algorithms. It’s SKLearncompliant, so it can be used in pipelines.
Successors should override methods
fit()
and_get_support_mask()
.Methods
fit
(x, *rest)Fit selector to a dataset. fit_transform
(X[, y])Fit to data, then transform it. get_params
([deep])Get parameters for this estimator. get_support
([indices])Get a mask, or integer index, of the features selected inverse_transform
(X)Reverse the transformation operation set_params
(**params)Set the parameters of this estimator. transform
(X)Reduce X to the selected features.

class
fsfc.base.
ClusteringFeatureSelector
(k)[source]¶ Bases:
fsfc.mixins.KBestSelectorMixin
,fsfc.base.BaseFeatureSelector
,sklearn.base.ClusterMixin
Clusters samples and simultaneously finds relevant features. Allows to transform dataset and select K best features according to features scores.
Parameters:  k: int
Number of features to select
Methods
fit
(x, *rest)fit_predict
(X[, y])Performs clustering on X and returns cluster labels. fit_transform
(X[, y])Fit to data, then transform it. get_params
([deep])Get parameters for this estimator. get_support
([indices])Get a mask, or integer index, of the features selected inverse_transform
(X)Reverse the transformation operation set_params
(**params)Set the parameters of this estimator. transform
(X)Reduce X to the selected features.

class
fsfc.base.
KBestFeatureSelector
(k)[source]¶ Bases:
fsfc.mixins.KBestSelectorMixin
,fsfc.base.BaseFeatureSelector
Base class for algorithms that selects K best features according to features scores.
Successors should override method
_calc_scores()
for computation of the score.Parameters:  k: int
Number of features to select
Methods
fit
(x, *rest)fit_transform
(X[, y])Fit to data, then transform it. get_params
([deep])Get parameters for this estimator. get_support
([indices])Get a mask, or integer index, of the features selected inverse_transform
(X)Reverse the transformation operation set_params
(**params)Set the parameters of this estimator. transform
(X)Reduce X to the selected features.