代码搜索:classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/450608/7480439
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
www.eeworm.com/read/450608/7480563
m testn.m
%TESTN Error estimate of discriminant for normal distribution.
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% E = TESTN(W,U,G,N)
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% INPUT
% W Trained classifier mapping
% U C x K dataset with C class means, labels and priors (default
www.eeworm.com/read/450608/7480574
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
www.eeworm.com/read/450608/7480579
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
www.eeworm.com/read/441245/7672604
m medianc.m
%MEDIANC Median combining classifier
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% W = MEDIANC(V)
% W = V*MEDIANC
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% INPUT
% V Set of classifiers
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% OUTPUT
% W Median combining classifier on V
%
% DESCRIPTION
% If V = [V
www.eeworm.com/read/441245/7672679
m knn_map.m
%KNN_MAP Map a dataset on a K-NN classifier
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% F = KNN_MAP(A,W)
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% INPUT
% A Dataset
% W K-NN classifier trained by KNNC
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% OUTPUT
% F Posterior probabilities
%
% DESCRIPTION
% Maps t
www.eeworm.com/read/441245/7672690
m classc.m
%CLASSC Convert mapping to classifier
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% W = CLASSC(W)
% W = W*CLASSC
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% INPUT
% W Any mapping or dataset
%
% OUTPUT
% W Classifier mapping or normalized dataset: outputs/features sum to 1
%
www.eeworm.com/read/441245/7672704
m prodc.m
%PRODC Product combining classifier
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% W = PRODC(V)
% W = V*PRODC
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% INPUT
% V Set of classifiers trained on the same classes
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% OUTPUT
% W Product combiner
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% DESCRIPTION
% It def
www.eeworm.com/read/441245/7672716
m contents.m
% Pattern Recognition Tools
% Version 4.1.4 11-Oct-2008
%
%Datasets and Mappings (just most important routines)
%---------------------
%dataset Define dataset from datamatrix and labels
%datasets
www.eeworm.com/read/441245/7673028
m meanc.m
%MEANC Mean combining classifier
%
% W = MEANC(V)
% W = V*MEANC
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% INPUT
% V Set of classifiers (optional)
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% OUTPUT
% W Mean combiner
%
% DESCRIPTION
% If V = [V1,V2,V3, ... ] is a s