代码搜索:classifier

找到约 4,824 项符合「classifier」的源代码

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m traincc.m

%TRAINCC Train combining classifier if needed % % W = TRAINCC(A,W,CCLASSF) % % INPUT % A Training dataset % W A set of classifiers to be combined % CCLASSF Combining classif
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m fisherc.m

%FISHERC Fisher's Least Square Linear Classifier % % W = FISHERC(A) % % INPUT % A Dataset % % OUTPUT % W Fisher's linear classifier % % DESCRIPTION % Finds the linear discriminant functio
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m testcost.m

function e = testcost(x,w,C,lablist) %TESTCOST compute the error using the cost matrix C % % E = TESTCOST(A,W,C,LABLIST) % E = TESTCOST(A*W,C,LABLIST) % E = A*W*TESTCOST([],C,LABLIST) % %
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m contents.m

% Bayesian classification. % % bayescls - Bayesian classifier with reject option. % bayesdf - Computes decision boundary of Bayesian classifier. % bayeserr - Computes Bayesian risk for 1D case with G
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m contents.m

% Visualization for pattern recognition. % % pandr - Visualizes solution of the Generalized Anderson's task. % pboundary - Plots decision boundary of given classifier in 2D. % pgauss
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m pandr.m

function varargout = pandr(model,distrib) % PANDR Visualizes solution of the Generalized Anderson's task. % % Synopsis: % h = pandr(model) % % Description: % It vizualizes solution of the Gen
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m svmclass.m

function [y,dfce] = svmclass(X,model) % SVMCLASS Support Vector Machines Classifier. % % Synopsis: % [y,dfce] = svmclass( X, model ) % % Description: % [y,dfce] = svmclass( X, model ) classifies inp
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java documentclassifier.java

/* Copyright (C) 2002 Univ. of Massachusetts Amherst, Computer Science Dept. This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit). http://www.cs.umass.edu/~mccallum/mallet Th
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java classifiertrainer.java

/* Copyright (C) 2002 Univ. of Massachusetts Amherst, Computer Science Dept. This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit). http://www.cs.umass.edu/~mccallum/mallet Th
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java classification.java

/* Copyright (C) 2002 Univ. of Massachusetts Amherst, Computer Science Dept. This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit). http://www.cs.umass.edu/~mccallum/mallet Th