代码搜索：classifier

找到约 4,824 项符合「classifier」的源代码

代码结果 4,824
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www.eeworm.com/read/150905/12249165

m meanc.m

%MEANC Mean combining classifier % % W = MEANC(V) % W = V*MEANC % % INPUT % V Set of classifiers (optional) % % OUTPUT % W Mean combiner % % DESCRIPTION % If V = [V1,V2,V3, ... ] is a s
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www.eeworm.com/read/150905/12249254

m ldc.m

%LDC Linear Bayes Normal Classifier (BayesNormal_1) % % W = LDC(A,R,S) % % INPUT % A Dataset % R,S Regularization parameters, 0
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www.eeworm.com/read/150905/12249331

m tree_map.m

%TREE_MAP Map a dataset by binary decision tree % % F = TREE_MAP(A,W) % % INPUT % A Dataset % W Decision tree mapping % % OUTPUT % F Posterior probabilities % % DESCRIPTION % Maps the dataset
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www.eeworm.com/read/150905/12249663

m testn.m

%TESTN Error estimate of discriminant for normal distribution. % % E = TESTN(W,U,G,N) % % INPUT % W Trained classifier mapping % U C x K dataset with C class means, labels and priors (default
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www.eeworm.com/read/150905/12249704

m prtestc.m

%PRTESTC Test routine for the PRTOOLS classifier % % This script tests a given, untrained classifier w, defined in the % workspace, e.g. w = my_classifier. The goal is to find out whether % w fulfill
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www.eeworm.com/read/150905/12249730

m prtools.m

% Pattern Recognition Tools % Version 4.0.14 04-Mar-2005 % %Datasets and Mappings (just most important routines) %--------------------- %dataset Define and retrieve dataset from datamatrix and lab
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www.eeworm.com/read/150749/12267237

m roc.m

function [AREA,SE,RESULT_S,FPR_ROC,TPR_ROC,TNa,TPa,FNa,FPa]=roc(RESULT,CLASS,fig) % Receiver Operating Characteristic (ROC) curve of a binary classifier % % >> [area, se, deltab, oneMinusSpec, sen
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www.eeworm.com/read/150749/12267383

m roc.m

function [AREA,SE,RESULT_S,FPR_ROC,TPR_ROC,TNa,TPa,FNa,FPa]=roc(RESULT,CLASS,fig) % Receiver Operating Characteristic (ROC) curve of a binary classifier % % >> [area, se, deltab, oneMinusSpec, sen
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www.eeworm.com/read/149739/12352642

m medianc.m

%MEDIANC Median combining classifier % % W = MEDIANC(V) % W = V*MEDIANC % % INPUT % V Set of classifiers % % OUTPUT % W Median combining classifier on V % % DESCRIPTION % If V = [V
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www.eeworm.com/read/149739/12352760

m classc.m

%CLASSC Convert mapping to classifier % % W = CLASSC(W) % W = W*CLASSC % % INPUT % W Any mapping or dataset % % OUTPUT % W Classifier mapping or normalized dataset: outputs/features sum to 1 %
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