PATTERN_MIN_MAX_NORM_CVIP

pattern_min_max_norm_cvip() - two csv files are input, training and test sets, and returns new csv files with the feature vectors normalized with min-max normalization.

Contents

SYNTAX

[normalized_file_tt,  normalized_file_tr] = pattern_min_max_norm_cvip(file_tt, file_tr, s_min,  s_max)

Input Parameters include :

Output Parameters include :

DESCRIPTION

This function gets the training set and the test set as input arguments and normalizes them using min-max normalization. Then the results are saved to two new CSV files and their names are returned as output.

REFERENCE

1. Scott E Umbaugh. DIGITAL IMAGE PROCESSING AND ANALYSIS: Applications with MATLAB and CVIPtools, 3rd Edition.

EXAMPLE

% Test set file

 file_tt = 'myTestVectors.CSV';

% Training set file

 file_tr = 'myTrainingVectors.CSV';

% Minimum perimeter

 s_min = 1;

% Maximum perimeter

 s_max = 10;

% Calling function

 [normalized_file_tt,  normalized_file_tr] = pattern_min_max_norm_cvip(file_tt, file_tr, s_min,  s_max)
normalized_file_tt =

min_max_myTestVectors.CSV


normalized_file_tr =

min_max_myTrainingVectors.CSV

CREDITS

Author: Mehrdad Alvandipour, March 2017
Copyright © 2017-2018 Scott E Umbaugh
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