代码搜索：classification

找到约 3,679 项符合「classification」的源代码

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py owc45tree.py

""" C4.5 C45 (classification tree) learner/classifier. icons/C45.png Janez Demsar (janez.demsar(@at@)fri.uni-lj.si)
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www.eeworm.com/read/192203/8399619

m rfclass.m

function [out] = RFClass(param,D1,D2,D3,D4,D5,D6) %! %! Description: %! %! RFClass implements Breiman's random forest algorithm for classification. %! It can also be used in unsupervised mode for
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www.eeworm.com/read/192203/8399671

m rfclass.m

function [out] = RFClass(param,D1,D2,D3,D4,D5,D6) %! %! Description: %! %! RFClass implements Breiman's random forest algorithm for classification. %! It can also be used in unsupervised mode for
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www.eeworm.com/read/442927/7641980

m fknn.m

function test_out = fknn(sample_in, sample_out, test_in, k, m) % FKNN Fuzzy k-nearest neighbor classification rule % % Usage: % TEST_OUT = FKNNR(SAMPLE_IN, SAMPLE_OUT, TEST_IN, K) % % SAMPLE_IN:
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www.eeworm.com/read/229812/4750169

gml rfsgen.gml

:I1.document structure :I1.GML summary :I1.sec :FIG place=inline frame=box. general elements pre GDOC elements &gml.GDOC sec='classification' (sec is optional) general elements &gml.F
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www.eeworm.com/read/271350/4229282

cc trainmlp.cc

const char *help = "\ progname: trainMLP.cc\n\ code2html: This program trains a MLP with sigmoid outputs for 2 class classification.\n\ version: Torch3 vision2.0, 2003-2005\n\ (c) Sebastien Marcel (ma
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www.eeworm.com/read/192735/8289541

m svm_multi_predk.m

function [beta, bo] = svm_multi_predK(X,Y,C,K) % SVM_MULTI_PREDK % % Support Vector Multi Classification % % USAGE: [beta, bo] = svm_multi_pred(X,Y,C,K) % % PARAMETERS: X - (m,d) matrix of m Tra
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www.eeworm.com/read/390840/8438228

m nnd10lc.m

function nnd10lc(cmd,arg1,arg2,arg3) % NND10LC Linear pattern classification demonstration. % Copyright 1994-2002 PWS Publishing Company and The MathWorks, Inc. % $Revision: 1.7 $ % First Versio
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txt cart_iris.txt

function CART_iris() DT_mean=1-DecisionT(datainput,datatarget,testinput,testtarget,error_value,trainnum); %决策树错误率 %for Classification Tree %训练决策树 function DT_mean=DecisionT(datainput,datatarget,t
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www.eeworm.com/read/384729/8848433

in makefile.in

TARGET=all INSTALL=@INSTALL@ RULES= classification.config \ attack-responses.rules backdoor.rules bad-traffic.rules chat.rules \ ddos.rules dns.rules dos.rules experimental.rules exploit.rules \
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