cvt.models.base_class.ConstrainedSMBase

class cvt.models.base_class.ConstrainedSMBase(n_subdims, n_gds_dims, normalize=False)

Base class of Constrained Subspace Method

__init__(n_subdims, n_gds_dims, normalize=False)
Parameters

  • n_subdims (int) – The dimension of subspace. it must be smaller than the dimension of original space.

  • n_gds_dims (int) – The dimension of Generalized Difference Subspace.

  • normalize (boolean, optional (default=True)) – If this is True, all vectors are normalized as |v| = 1.

Methods

__init__(n_subdims, n_gds_dims[, normalize])

param n_subdims

The dimension of subspace. it must be smaller than the dimension of original space.

fit(X, y)

Fit the model using the given data and parameters

get_params([deep])

Get parameters for this estimator.

predict(X)

Predict classes

predict_proba(X)

Predict class probabilities

proba2class(proba)

score(X, y[, sample_weight])

Return the mean accuracy on the given test data and labels.

set_params(**parameters)

Set the parameters of this estimator.

Attributes

param_names