代码搜索:classification

找到约 3,679 项符合「classification」的源代码

代码结果 3,679
www.eeworm.com/read/255755/12057443

m getcost.m

%GETCOST Get classification cost matrix % % [COST,LABLIST] = GETCOST(A) % % Returns the classification cost matrix as defined for the dataset A. % An empty cost matrix is interpreted as equal costs f
www.eeworm.com/read/255755/12058057

m getcost.m

%GETCOST Get classification cost matrix % % [COST,LABLIST] = GETCOST(W) % % Returns the classification cost matrix as set in the classifier W. % An empty cost matrix is interpreted as equal costs for
www.eeworm.com/read/253950/12173998

htm demtrain.htm

Netlab Reference Manual demtrain demtrain Purpose Demonstrate training of MLP network. Synopsis demtrain
www.eeworm.com/read/339991/12188628

m contents.m

% Support Vector Machine Toolbox % Version 2.0-Aug-1998 % % Support Vector Classification % % svc - Calculate support vectors for classification % svcplot - Plot 2 dimensional clas
www.eeworm.com/read/150905/12248306

m labeld.m

%LABELD Find labels of classification dataset (perform crisp classification) % % LABELS = LABELD(Z) % LABELS = Z*LABELD % LABELS = LABELD(A,W) % LABELS = A*W*LABELD % LABELS = LABELD(Z,THRE
www.eeworm.com/read/150905/12248563

m getcost.m

%GETCOST Get classification cost matrix % % [COST,LABLIST] = GETCOST(A) % % Returns the classification cost matrix as defined for the dataset A. % An empty cost matrix is interpreted as equal costs f
www.eeworm.com/read/150905/12249359

m getcost.m

%GETCOST Get classification cost matrix % % [COST,LABLIST] = GETCOST(W) % % Returns the classification cost matrix as set in the classifier W. % An empty cost matrix is interpreted as equal costs for
www.eeworm.com/read/150905/12250181

htm demtrain.htm

Netlab Reference Manual demtrain demtrain Purpose Demonstrate training of MLP network. Synopsis demtrain
www.eeworm.com/read/252980/12251844

readme

Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
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m contents.m

% Bayesian classification. % % bayescls - Bayesian classifier with reject option. % bayesdf - Computes decision boundary of Bayesian classifier. % bayeserr - Computes Bayesian risk for 1D case with G