代码搜索:classifier

找到约 4,824 项符合「classifier」的源代码

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m fldqp.m

function model = fldqp(data) % FLDQP Fisher Linear Discriminat using Quadratic Programming. % % Synopsis: % model = fldqp( data ) % % Description: % This function computes the binary linear classifi
www.eeworm.com/read/310621/13648609

m adaboost.m

function [H,alpha]=AdaBoost(X,Y,C,T,WLearner) % AdaBoost % Train a strong classifier using several weak ones % % Input % X - samples % Y - label of samples - % 1 - belong to
www.eeworm.com/read/134901/5891566

m fldqp.m

function model = fldqp(data) % FLDQP Fisher Linear Discriminat using Quadratic Programming. % % Synopsis: % model = fldqp( data ) % % Description: % This function computes the binary linear classifi
www.eeworm.com/read/493294/6399955

m dd_setfn.m

function w = dd_setfn(w,a,thr) %DD_SETFN Set the threshold to a specific FN rate % % W2 = DD_SETFN(W,A,THR) % % The data of classifier W is copied to classifier W2, only the % threshold value is c
www.eeworm.com/read/493294/6400452

m multic.m

%MULTIC Make a multi-class classifier % % W = MULTIC(A,V) % % Train the (untrained!) one-class classifier V on each of the classes % in A, and combine it to a multi-class classifier W. If an object
www.eeworm.com/read/493294/6400465

m is_occ.m

%IS_OCC True for one-class classifiers % % IS_OCC(W) returns true if the classifier W is a one-class classifier, % outputting only classes 'target' and/or 'outlier' and having a % structure with t
www.eeworm.com/read/492695/6419388

m display.m

function display(net) fprintf(1,'\nsupport vector classifier:\n\n'); fprintf(1,' kernel = %s\n', char(net.kernel)); fprintf(1,' bias = %f\n', net.bias); fprintf(1,' sv = %s\n', m
www.eeworm.com/read/492400/6422233

m dd_setfn.m

function w = dd_setfn(w,a,thr) %DD_SETFN Set the threshold to a specific FN rate % % W2 = DD_SETFN(W,A,THR) % % The data of classifier W is copied to classifier W2, only the % threshold value is c
www.eeworm.com/read/492400/6422301

m is_occ.m

%IS_OCC True for one-class classifiers % % IS_OCC(W) returns true if the classifier W is a one-class classifier, % outputting only classes 'target' and/or 'outlier' and having a % structure with t
www.eeworm.com/read/482720/6621670

m contents.m

% OSU Support Vector Machines (SVMs) Toolbox % version 3.00, Feb. 2002 % % The core of this toolbox is based on Dr. Lin's Lib SVM version 2.33 % For more details, please see: % http://www.csie.n