PATTERN_EUCLIDEAN_CVIP
pattern_euclidean_cvip() - takes two csv files as input, test and training set, then calculates the Euclidean distance metric by comparing each vector in the test set to each in the training set
Contents
SYNTAX
d = pattern_euclidean_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 :
- d - A matrix containing the distances between each vector in the test set to each vector in the training set. Each column represents a vector in training set. Each row represents a vector in test set.
DESCRIPTION
Using euclidean metric, the function calculates the distance between the vectors in training set and the test set. The distances are returned in a matrix form whose rows represent the test vectors and columns represent the training vectors.
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 d = pattern_euclidean_cvip(file_tt, file_tr)
d = 25.0000 20.3961 22.4722 18.3576 12.0830 12.0416 12.0416 27.2947 25.4951 29.0000 15.5242 12.8062 16.2788 16.2788 21.3776 17.8885 20.8087 13.0000 7.0711 8.5440 8.5440 28.1780 26.2488 29.6985 16.4924 13.6015 16.9706 16.9706 20.6155 17.4929 20.6155 11.7047 6.0000 8.0623 8.0623 23.0217 18.6815 21.0238 16.1245 9.8489 10.0000 10.0000 0 6.4031 8.9443 12.7279 14.8661 13.0384 13.0384 6.4031 0 4.1231 13.6015 12.7279 9.4340 9.4340 8.9443 4.1231 0 17.7200 16.4012 12.7279 12.7279 12.7279 13.6015 17.7200 0 6.4031 8.9443 8.9443 14.8661 12.7279 16.4012 6.4031 0 4.1231 4.1231 13.0384 9.4340 12.7279 8.9443 4.1231 0 0
CREDITS
Author: Mehrdad Alvandipour, March 2017
Copyright © 2017-2018 Scott
E Umbaugh
For updates visit CVIP Toolbox Website
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