PATTERN_SND_NORM_CVIP
pattern_snd_norm_cvip() - two csv files are input, training and test sets, and returns new csv files with the feature vectors normalized with standard normal density (snd) normalization.
Contents
SYNTAX
[normalized_file_tt, normalized_file_tr] = pattern_snd_norm_cvip(file_tt, file_tr)
Input Parameters include :
- file_tt - Name of the test set file. A CSV file with a predefined structure.
- file_tr - Name of the training set file. A CSV file with a predefined structure.
Output Parameters include :
- normalized_file_tt - A string containing the name of the normalized test file.It is the same name as file_tt with the prefix SND_.
- normalized_file_tr - A string containing the name of the normalized training file.It is the same name as file_tr with the prefix SND_.
DESCRIPTION
This function gets the training set and the test set as input arguments and normalizes them using the Standard Normalization Density (SND) normalization method. 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'; % Calling function [normalized_file_tt, normalized_file_tr] = pattern_snd_norm_cvip(file_tt, file_tr)
normalized_file_tt = SND_myTestVectors.CSV normalized_file_tr = SND_myTrainingVectors.CSV
CREDITS
Author: Mehrdad Alvandipour, March 2017
Copyright © 2017-2018 Scott
E Umbaugh
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