plusml::BinaryLogisticRegression Class Reference

Basic binary logistic regression. More...

#include <binary_logistic_regression.h>

Public Member Functions
	BinaryLogisticRegression (uint64_t features, bool bias_enabled=true)
	Constructor for BinaryLogisticRegression class.
uint64_t	Features () const
	Get number of features in each sample for the model.
Eigen::MatrixXf	Parameters () const
	Get current parameters of the model.
void	SetParameters (const Eigen::MatrixXf &parameters)
	Set desired parameters for the model.
void	FitSGD (const Eigen::MatrixXf &samples, const Eigen::MatrixXf &targets, float learning_rate, uint64_t batch_size, uint64_t epochs)
	Fit model using stochastic gradient descent with given hyperparameters.
Eigen::MatrixXf	Predict (Eigen::MatrixXf samples)
	Get predictions for a given matrix of samples.

Detailed Description

Basic binary logistic regression.

Constructor & Destructor Documentation

BinaryLogisticRegression()

plusml::BinaryLogisticRegression::BinaryLogisticRegression ( uint64_t features, bool bias_enabled = true )

explicit

Constructor for BinaryLogisticRegression class.

Parameters

features	Number of features in each sample
bias_enabled	Specifies whether to use bias or not

Initializes model's parameters to zero

Member Function Documentation

Features()

uint64_t plusml::BinaryLogisticRegression::Features

(

)

const

Get number of features in each sample for the model.

Returns

Number of features in each sample for the model

FitSGD()

void plusml::BinaryLogisticRegression::FitSGD	(	const Eigen::MatrixXf &	samples,
		const Eigen::MatrixXf &	targets,
		float	learning_rate,
		uint64_t	batch_size,
		uint64_t	epochs )

Fit model using stochastic gradient descent with given hyperparameters.

Parameters

samples	Matrix of samples (MxN where M is number of samples and N is number of features in each sample)
targets	Matrix of targets (Mx1 where M is number of samples)
learning_rate	Learning rate for SGD
batch_size	Batch size for SGD
epochs	Number of epochs for SGD

Parameters()

Eigen::MatrixXf plusml::BinaryLogisticRegression::Parameters

(

)

const

Get current parameters of the model.

Returns

Parameters matrix

Predict()

Eigen::MatrixXf plusml::BinaryLogisticRegression::Predict

(

Eigen::MatrixXf

samples

)

Get predictions for a given matrix of samples.

Parameters

samples

Matrix of samples (MxN where M is number of samples and N is number of features in each sample)

Returns

Matrix of predicted classes (Mx1 where M is number of samples)

SetParameters()

void plusml::BinaryLogisticRegression::SetParameters

(

const Eigen::MatrixXf &

parameters

)

Set desired parameters for the model.

Parameters

parameters

Matrix representing parameters to set

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The documentation for this class was generated from the following files:

• include/PlusML/binary_logistic_regression.h
• src/binary_logistic_regression.cpp