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linear_regression Class Reference

#include <linear_regression.h>

Inheritance diagram for linear_regression:

List of all members.

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Detailed Description

Implementation of a linear regression.

Public Member Functions

• linear_regression (unsigned int in_rows=1)
• ~linear_regression (void)
• int apply (const double *S, double *X)
• void reset ()
• int importRepresentation (const double *rep, int rep_length)
• double * exportRepresentation (int *rep_length)
• string getFormatDescription ()

Private Attributes

• double * regression_coefficients

  Vector of linear-regression coefficients.
  
  

Friends

• class csimClassInfoDB

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Constructor & Destructor Documentation

linear_regression::linear_regression (  unsigned int    in_rows = 1 )

Constructs a new linear regression algorithm. Parameters: in_rows  Number of rows in each input vector.

linear_regression::~linear_regression (  void    )

Frees the memory.

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Member Function Documentation

int linear_regression::apply (  const double *    S, double *    X )  [virtual]

Applies the currently learned function to the filtered and preprocessed input vector. Parameters: S  State of the liquid (= filtered and preprocessed response of the neural microcircuit). X  Target pointer where to save the result. Returns: -1 if an error occured, 1 for success. Implements Algorithm.

double * linear_regression::exportRepresentation (  int *    rep_length )  [virtual]

Exports the representation of this algorithm for use in external objects. Parameters: rep_length  Length of the representation vector. Returns: A list of parameters that represent the algorithm. Warning: Do not forget to free the memory reserved for the representation! Implements Algorithm.

string linear_regression::getFormatDescription (    )  [virtual]

Returns a textual description of the representation format for import/export - Representation. Implements Algorithm.

int linear_regression::importRepresentation (  const double *    rep, int    rep_length )  [virtual]

Imports the data from an externally (e.g. Matlab) trained algorithm. Parameters: rep  Representation of the algorithm as a double vector. rep_length  Length of the representation vector. Returns: -1 if an error occured, 1 for success. Implements Algorithm.

void linear_regression::reset (    )  [virtual]

Resets the information stored within the algorithm. Reimplemented from Algorithm.

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