代码搜索:classifier

找到约 4,824 项符合「classifier」的源代码

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c bcx.c

/*---------------------------------------------------------------------- File : bcx.c Contents: naive and full Bayes classifier execution Author : Christian Borgelt History : 1998.12.08 fi
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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
www.eeworm.com/read/280595/10311830

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
www.eeworm.com/read/280531/10322474

m demogentleboost.m

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Simple demo of Gentle Boost with stumps and 2D data % % % Implementation of gentleBoost. The algorithm is describe
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m rbfdemo.m

echo off % RBFDEMO demonstration for using nonlinear SVM classifier % with a RBF kernel. echo on; clc % RBFDEMO demonstration for using nonlinear SVM classifier % with a RBF kernel. %#####
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m c_svcdemo.m

% ------- OSU C-SVM CLASSIFIER TOOLBOX Demonstrations--- % % 1) Construct a linear SVM Classifier and test it % 2) Construct a nonlinear SVM Classifier (polynomial kernel) and t
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m svcdemo.m

% ------- OSU SVM CLASSIFIER TOOLBOX Demonstrations--- % % 1) Construct a linear SVM Classifier and test it % 2) Construct a nonlinear SVM Classifier (polynomial kernel) and tes
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m u_clademo.m

echo off % CLADEMO demonstration for using a contructed SVM classifier to classify % input patterns % echo on; % % % NOTICE: please first run any of the first three demonstrations before %