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m smosvctutor.m

function tutor = smosvctutor1(arg) % SMOSVCTUTOR % % Construct a tutor object for training support vector classifiers using the % sequential minimal optimisation algorithm. % % Examples: % %
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asv smosvctutor.asv

function tutor = smosvctutor1(arg) % SMOSVCTUTOR % % Construct a tutor object for training support vector classifiers using the % sequential minimal optimisation algorithm. % % Examples: % %
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m smosvctutor1.m

function tutor = smosvctutor1(arg) % SMOSVCTUTOR % % Construct a tutor object for training support vector classifiers using the % sequential minimal optimisation algorithm. % % Examples: % %
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www.eeworm.com/read/483114/6609758

asv smosvctutor.asv

function tutor = smosvctutor1(arg) % SMOSVCTUTOR % % Construct a tutor object for training support vector classifiers using the % sequential minimal optimisation algorithm. % % Examples: % %
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www.eeworm.com/read/353326/10454044

m roc.m

function roc(x,y) % ROC - Receiver Operating Characteristics. % The ROC graphs are a useful tecnique for organizing classifiers and % visualizing their performance. ROC graphs are commonly used in
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www.eeworm.com/read/251501/12340729

1st readme.1st

This package contains a set of speaker recogntion research tools, they can also be used as general classifiers. Roughtly speaking, the utilities can be divided into the following categories: A. f
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www.eeworm.com/read/130490/14189956

c holders.c

/* Copyright (C) 2001-2002 Mikael Ylikoski * See the accompanying file "README" for the full copyright notice */ /** * @file * Loads and keeps track of available classifiers and stemmers. * * @a
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java editablebayesnet.java

package weka.classifiers.bayes.net; /* * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Softw
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www.eeworm.com/read/130490/14190055

c multi_one.c

/* Copyright (C) 2001-2002 Mikael Ylikoski * See the accompanying file "README" for the full copyright notice */ /** * @file * Multi class classification for binary classifiers. * * Wrapper to c
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www.eeworm.com/read/13911/286735

m osusvmdemo.m

% ------- OSU SVM CLASSIFIER TOOLBOX Demonstrations--- % % 1) Demonstrations of using C-SVM Classifers. % 2) Demonstrations of using u-SVM Classifiers % 3) Demonstration
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