Linear Denoiser

Module for the linear denoiser.

class breze.learn.lde.LinearDenoiser(p_dropout)

Class that represents linear denoisers.

LinearDenoisers (LDEs) were later also named Marginalized Denoising AutoEncoders.

Introduced in [R1].

References

[R1]	(1, 2) Xu, Zhixiang Eddie, Kilian Q. Weinberger, and Fei Sha. “Rapid feature learning with stacked linear denoisers.” arXiv preprint arXiv:1105.0972 (2011).

Methods

fit(X)	Fit the parameters of the model.
transform(X)	Transform data according to the model.

__init__(p_dropout)

Create a LinearDenoiser object.

Parameters:

p_dropout : float

Probability of an input being dropped out.

fit(X)

Fit the parameters of the model.

Parameters:

X : array_like

An array of shape (n, d) where n is the number of data points and d the input dimensionality.

transform(X)

Transform data according to the model.

Parameters:

X : array_like

An array of shape (n, d) where n is the number of data points and d the input dimensionality.

Returns:

Y : array_like

An array of shape (n, d) where n is the number of data points and d the input dimensionality.