代码搜索：classification

找到约 3,679 项符合「classification」的源代码

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m prex_logdens.m

%PREX_LOGDENS PRTools example on density based classifier improvement % % This example shows the use and results of LOGDENS for improving % the classification in the tail of the distributions h
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www.eeworm.com/read/150905/12248304

m prex_logdens.m

%PREX_LOGDENS PRTools example on density based classifier improvement % % This example shows the use and results of LOGDENS for improving % the classification in the tail of the distributions h
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www.eeworm.com/read/149739/12352677

m prex_logdens.m

%PREX_LOGDENS PRTools example on density based classifier improvement % % This example shows the use and results of LOGDENS for improving % the classification in the tail of the distributions h
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www.eeworm.com/read/130490/14190122

xml ref_selectd.xml

selectd 8 selectd email classification daemon
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www.eeworm.com/read/429426/1948886

py cb-splitconstructor.py

# Description: Shows how to derive a Python class from orange.TreeSplitConstructor # Category: classification, decision trees, callbacks to Python # Classes: TreeSplitConstructor, Classifier,
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www.eeworm.com/read/429426/1948915

py cb-stopcriteria.py

# Description: Shows how to derive a Python class from orange.TreeStopCriteria # Category: classification, callbacks to Python # Classes: TreeStopCriteria # Uses: lenses # Referenced
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www.eeworm.com/read/289680/8534995

m getkernel.m

function kernel = getkernel(net) % GETKERNEL % % Accessor method returning the kernel used in a support vector classification % network. % % ker = getkernel(net) % % File : @svc/
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www.eeworm.com/read/188280/8552140

m getkernel.m

function kernel = getkernel(net) % GETKERNEL % % Accessor method returning the kernel used in a support vector classification % network. % % ker = getkernel(net) % % File : @svc/
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www.eeworm.com/read/289334/8558642

m contents.m

% Miscellaneous functions for STPRtoolbox. % % adaboost - AdaBoost algorithm. % adaclass - AdaBoost classifier. % cerror - Computes classification error. % crossval - Partions data
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www.eeworm.com/read/386050/8767467

m polyc.m

%POLYC Polynomial Classification % % W = polyc(A,CLASSF,N,S) % % INPUT % A Dataset % CLASSF Untrained classifier (optional; default: FISHERC) % N Degree of polynomial (optional;
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