ANNClassifier Class Reference

#include <Classifier.h>

Inheritance diagram for ANNClassifier:

Public Member Functions
	ANNClassifier (double _eta, int _n_iter)
virtual Matrix< double >	activation (const Matrix< double > &)=0
virtual Matrix< double >	netInput (const Matrix< double > &)=0
virtual double	costFunction (const Matrix< double > &)=0
Public Member Functions inherited from Classifier
	Classifier ()
void	initialize_weights (size_t numRows, size_t numColumns=1)
void	update_weights (const Matrix< double > &update, const Matrix< double > &delta)
Matrix< double >	transform (const Matrix< double > &in) override
Public Member Functions inherited from Predictor
virtual void	fit (const Matrix< double > &X, const Matrix< double > &y)=0
virtual Matrix< double >	predict (const Matrix< double > &)=0
virtual Matrix< double >	transform (const Matrix< double > &)=0

Protected Attributes
double	eta
	Learning rate. More...
int	n_iter
	number epochs More...
Protected Attributes inherited from Classifier
bool	w_initialized = false
	flag to initialize weights only once More...

Additional Inherited Members
Public Attributes inherited from Classifier
Matrix< double >	weights
	Vector holding weights. More...
Matrix< double >	costs
	Vector holding classification error per epoch. More...

Detailed Description

Artificial Neural Network Classifier interface.

Adds interface for activation, cost and net-input functions. As well as learning rate and constant for number of training epochs.

Constructor & Destructor Documentation

ANNClassifier()

ANNClassifier::ANNClassifier ( double  _eta, int  _n_iter  )

inline

Member Function Documentation

activation()

virtual Matrix< double > ANNClassifier::activation ( const Matrix< double > &  )

pure virtual

Activates a given input

Returns

Implemented in AdalineGD, AdalineSGD, LogRegSGD, and Perceptron.

costFunction()

virtual double ANNClassifier::costFunction ( const Matrix< double > &  )

pure virtual

calculates the current cost if unused override returning 0

Implemented in LogRegSGD, AdalineGD, AdalineSGD, and Perceptron.

netInput()

virtual Matrix< double > ANNClassifier::netInput ( const Matrix< double > &  )

pure virtual

calculates the net-input (aka output) this is mostly the derivative of activation

Returns

Implemented in AdalineGD, AdalineSGD, LogRegSGD, and Perceptron.

Member Data Documentation

eta

double ANNClassifier::eta

protected

Learning rate.

n_iter

int ANNClassifier::n_iter

protected

number epochs

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

• include/math/ds/Classifier.h