Classification#

Module with classes to perform classification of functional data.

Nearest Neighbors#

This module contains nearest neighbors estimators to perform classification. In the examples K-nearest neighbors classification and Radius neighbors classification it is explained the basic usage of these estimators.

skfda.ml.classification.KNeighborsClassifier()

Classifier implementing the k-nearest neighbors vote.

skfda.ml.classification.RadiusNeighborsClassifier()

Classifier implementing a vote among neighbors within a given radius.

Nearest Centroid#

This module contains nearest centroid estimators to perform classification.

skfda.ml.classification.NearestCentroid([...])

Nearest centroid classifier for functional data.

skfda.ml.classification.DTMClassifier(...[, ...])

Distance to trimmed means (DTM) classification.

Depth#

This module contains depth based estimators to perform classification.

skfda.ml.classification.MaximumDepthClassifier([...])

Maximum depth classifier for functional data.

skfda.ml.classification.DDClassifier(degree)

Depth-versus-depth (DD) classifer for functional data.

skfda.ml.classification.DDGClassifier(*[, ...])

Generalized depth-versus-depth (DD) classifier for functional data.

Logistic regression#

Classifier based on logistic regression.

skfda.ml.classification.LogisticRegression([...])

Logistic Regression classifier for functional data.

Functional quadratic discriminant analysis#

Classifier based on the quadratic discriminant analysis.

skfda.ml.classification.QuadraticDiscriminantAnalysis(...)

Functional quadratic discriminant analysis.