Perceptron Class Reference

#include <Perceptron.h>

Inheritance diagram for Perceptron:

Public Member Functions
	Perceptron (double _eta=0.01, int iter=10)
void	fit (const Matrix< double > &X, const Matrix< double > &y) override
Matrix< double >	netInput (const Matrix< double > &X) override
Matrix< double >	activation (const Matrix< double > &X) override
Matrix< double >	predict (const Matrix< double > &X) override
double	costFunction (const Matrix< double > &X) override
Public Member Functions inherited from ANNClassifier
	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
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

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...
Protected Attributes inherited from ANNClassifier
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...

Detailed Description

Represents Perceptron definition by Frank Rosenblatt

Wikipedia

Essentially it can be used to build binary classification One might for example want to replace some very complex binary operation which is a combination of several broad operations like OR|AND|XOR|NOT ...

In order to use the perceptron classifier one needs access to the full set of possible transformations.

THIS IS NOT A PREDICTOR

Mainly implemented for academic use

Examples

ds/TestPerceptron.cpp.

Constructor & Destructor Documentation

Perceptron()

Perceptron::Perceptron ( double  _eta = 0.01, int  iter = 10  )

inlineexplicit

default constructor

Parameters

_eta
iter

Member Function Documentation

activation()

Matrix< double > Perceptron::activation ( const Matrix< double > &  X )

inlineoverridevirtual

activate given input

Parameters

X

Returns

Implements ANNClassifier.

costFunction()

double Perceptron::costFunction ( const Matrix< double > &  X )

inlineoverridevirtual

cost function override, don't use!

Parameters

X

Returns

Implements ANNClassifier.

fit()

void Perceptron::fit ( const Matrix< double > &  X, const Matrix< double > &  y  )

inlineoverridevirtual

Parameters

X	array-like with the shape: [n_samples, n_features]
y	array-like with shape: [n_samples, 1]

Returns

this

Implements Predictor.

netInput()

Matrix< double > Perceptron::netInput ( const Matrix< double > &  X )

inlineoverridevirtual

calculates net input

\[ X * weights + b \]

Parameters

X

Returns

Implements ANNClassifier.

predict()

Matrix< double > Perceptron::predict ( const Matrix< double > &  X )

inlineoverridevirtual

predict class of given input

Parameters

X

Returns

Implements Predictor.

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

• include/math/ds/Perceptron.h