代码搜索：classification

找到约 3,679 项符合「classification」的源代码

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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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www.eeworm.com/read/13911/286887

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/175689/5343516

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/429426/1948660

py tree8.py

# Description: Builds a classification tree, and prunes it using minimal error # prunning with different values of parameter m. Prints # out m and the size of the tree. #
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www.eeworm.com/read/429426/1948831

py classifierbylookuptable.py

# Description: Shows how to construct and use classifiers by lookup table to construct new features from the existing # Category: classification, lookup classifiers, constructive induction, featur
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www.eeworm.com/read/429426/1948837

py cb-classifier.py

# Description: Shows how to derive a Python classifier from orange.Classifier # Category: classification, callbacks to Python # Classes: Classifier # Uses: lenses # Referenced: call
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www.eeworm.com/read/429426/1948900

py cb-descender.py

# Description: Shows how to derive a tree descender from orange.TreeDescender # Category: classification, decision trees, callbacks to Python # Classes: TreeDescender # Uses: lenses
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www.eeworm.com/read/428780/1954190

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/411379/2188965

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/409299/2234788

svn-base leastsquaresclassifier.m.svn-base

function [trainInfo, testInfo, classifierInfo] = leastSquaresClassifier(trainX, trainY, testX, params); %A function to compute least squares classification on the data on binary labels. No bias term
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