代码搜索:classifier

找到约 4,824 项符合「classifier」的源代码

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www.eeworm.com/read/172172/9722108

m code.m

function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args) % Encode and decode a multi-class classification task into multiple binary cl
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h declare.h

/* XCSR_DE1.0 * -------------------------------------------------------- * Learning classifier system based on accuracy in dynamic environments * * by Huong Hai (Helen) Dam * z3140959@itee.adfa.
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m bay_modoutclass.m

function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay) % Estimate the posterior class probabilities of a binary classifier using Bayesian inference % % >> [Ppos, Pneg] = bay
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asv ls_svm2.asv

% 支持向量机最小二乘算法(LS-SVM)--可用于分类和回归??? % function [ output_args ] = SvmLs( input_args ) clc clear close all m = 4; % 样本维数 TrainSample = [1+rand(m,5),2+rand(m,5),3+rand(m,5),4+rand(m,5)]; TrainTa
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m code.m

function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args) % Encode and decode a multi-class classification task into multiple binary cl
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asv code.asv

function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args) % Encode and decode a multi-class classification task into multiple binary cl
www.eeworm.com/read/415313/11076347

m test_classify.m

% Test_Classifiy: the main module for MATLABArsenal % % Parameter: % classifier: the classifier description string % Example: test_classify('classify -t DataExample1.txt -sf 1 -- LibSVM % -Ke
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m bayesdf.m

function quad_model=bayesdf(model) % BAYESDF Computes decision boundary of Bayesian classifier. % % Synopsis: % quad_model = bayesdf(model) % % Description: % This function computes parameter
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m contents.m

% Miscellaneous functions for STPRtoolbox. % % adaboost - AdaBoost algorithm. % adaclass - AdaBoost classifier. % cerror - Computes classification error. % crossval - Partions data
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txt see5sam.txt

To run See5Sam.exe from a command prompt window: * Make sure that you have run See5 on your application to construct the kind of classifier that you want to use. * Put See5Sam.exe in the