cvt.models.base_class.SMBase¶

class cvt.models.base_class.SMBase(n_subdims, normalize=False, faster_mode=False)¶

Base class of Subspace Method

__init__(n_subdims, normalize=False, faster_mode=False)¶

Parameters

n_subdims (int) – The dimension of subspace. it must be smaller than the dimension of original space.
normalize (boolean, optional (default=True)) – If this is True, all vectors are normalized as |v| = 1

Methods

`__init__`(n_subdims[, normalize, faster_mode])	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