代码搜索：classifier

找到约 4,824 项符合「classifier」的源代码

代码结果 4,824
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www.eeworm.com/read/328782/3436181

h cucontrol_warmer.h

// {{{RME classifier 'Logical View::ControlUnits::CUControl_Warmer' #ifndef rtg_CUControl_Warmer_H #define rtg_CUControl_Warmer_H #ifdef PRAGMA #pragma interface "rtg/CUControl_Warmer.h" #endif #in
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www.eeworm.com/read/328782/3436198

h warmnonemptypot_test.h

// {{{RME classifier 'Logical View::TestHarnesses::MarkI_Tests::Scenarios_MarkI::WarmNonEmptyPot_Test' #ifndef rtg_WarmNonEmptyPot_Test_H #define rtg_WarmNonEmptyPot_Test_H #ifdef PRAGMA #pragma int
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www.eeworm.com/read/430506/1929492

m oaoclass.m

function [labels,votes] = oaoclass(data,model) % OAOCLASS One-Against-One SVM classifier. % [labels,votes] = oaoclass(data,model) % % Inputs: % data [dim x num_data] data to be classified. % Model [
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www.eeworm.com/read/429426/1949328

py owknn.py

""" k Nearest Neighbours K-nearest neighbours learner/classifier. icons/kNearestNeighbours.png Janez Demsar (janez.demsar(@at@)fri.uni
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www.eeworm.com/read/429426/1949336

py owmajority.py

""" Majority Majority class learner/classifier. icons/Majority.png Janez Demsar (janez.demsar(@at@)fri.uni-lj.si)
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www.eeworm.com/read/428780/1954288

m svmtrain.m

function net = svmtrain(net, X, Y, alpha0, dodisplay) % SVMTRAIN - Train a Support Vector Machine classifier % % NET = SVMTRAIN(NET, X, Y) % Train the SVM given by NET using the training data X w
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www.eeworm.com/read/396844/2407834

m knn.m

function [C,P]=knn(d, Cp, K) %KNN K-Nearest Neighbor classifier using an arbitrary distance matrix % % [C,P]=knn(d, Cp, [K]) % % Input and output arguments ([]'s are optional): % d (matrix)
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www.eeworm.com/read/382446/2636757

java tfidfclassifiertrainertest.java

package com.aliasi.test.unit.classify; import com.aliasi.classify.TfIdfClassifierTrainer; import com.aliasi.classify.Classification; import com.aliasi.classify.Classifier; import com.aliasi.classify.
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www.eeworm.com/read/373460/2761926

m oaoclass.m

function [labels,votes] = oaoclass(data,model) % OAOCLASS One-Against-One SVM classifier. % [labels,votes] = oaoclass(data,model) % % Inputs: % data [dim x num_data] data to be classified. % Model [
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www.eeworm.com/read/359369/2978471

m knnfwd.m

function [y, l] = knnfwd(net, x) %KNNFWD Forward propagation through a K-nearest-neighbour classifier. % % Description % [Y, L] = KNNFWD(NET, X) takes a matrix X of input vectors (one vector % p
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