PATTERN_VECTOR_INNER_PRODUCT_CVIP
pattern_vector_inner_product_cvip() - takes two csv files as input, test and training set, then calculates the normalized vector inner product metric by comparing each vector in the test set to each in the training set.
Contents
SYNTAX
d = pattern_vector_inner_product_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 inner product 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 normalized vector inner product, the function calculates the similarity 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_vector_inner_product_cvip(file_tt, file_tr)
d =
Columns 1 through 6
387 458 535 207 278 355
166 180 206 94 108 134
415 450 515 235 270 335
140 159 184 77 96 121
422 448 510 242 268 330
420 477 552 231 288 363
1037 983 1085 632 578 680
983 970 1083 587 574 687
1085 1083 1213 644 642 772
632 587 644 389 344 401
578 574 642 344 340 408
680 687 772 401 408 493
Column 7
355
134
335
121
330
363
680
687
772
401
408
493
CREDITS
Author: Mehrdad Alvandipour, March 2017
Copyright © 2017-2018 Scott
E Umbaugh
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