代码搜索:classifier

找到约 4,824 项符合「classifier」的源代码

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www.eeworm.com/read/451547/7461984

m dd_ex8.m

% Show the interactive capabilities of the plotroc command. % % Generate some simple data, train a one-class classifier, make a % scatterplot with the classifier and plot an ROC curve. Now it is % pos
www.eeworm.com/read/450608/7480102

m baggingc.m

%BAGGINGC Bootstrapping and aggregation of classifiers % % W = BAGGINGC (A,CLASSF,N,ACLASSF,T) % % INPUT % A Training dataset. % CLASSF The base classifier (default: nmc) % N
www.eeworm.com/read/450608/7480117

m knn_map.m

%KNN_MAP Map a dataset on a K-NN classifier % % F = KNN_MAP(A,W) % % INPUT % A Dataset % W k-NN classifier trained by KNNC % % OUTPUT % F Posterior probabilities % % DESCRIPTION % Maps t
www.eeworm.com/read/450608/7480119

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;
www.eeworm.com/read/450608/7480154

m parsc.m

%PARSC Parse classifier % % PARSC(W) % % Displays the type and, for combining classifiers, the structure of the % mapping W. % % See also MAPPINGS % Copyright: R.P.W. Duin, duin@ph.tn.tudelft.nl
www.eeworm.com/read/450608/7480157

m parallel.m

%PARALLEL Combining classifiers in different feature spaces % % WC = PARALLEL(W1,W2,W3, ....) or WC = [W1;W2;W3; ...] % WC = PARALLEL({W1;W2;W3; ...}) or WC = [{W1;W2;W3; ...}] % WC = PARALL
www.eeworm.com/read/450608/7480382

m nmsc.m

%NMSC Nearest Mean Scaled Classifier % % W = NMSC(A) % % INPUT % A Trainign dataset % % OUTPUT % W Nearest Mean Scaled Classifier mapping % % DESCRIPTION % Computation of the linear discrim
www.eeworm.com/read/450608/7480582

m traincc.m

%TRAINCC Train combining classifier if needed % % W = TRAINCC(A,W,CCLASSF) % % INPUT % A Training dataset % W A set of classifiers to be combined % CCLASSF Combining classif
www.eeworm.com/read/450608/7480619

m testcost.m

function e = testcost(x,w,C,lablist) %TESTCOST compute the error using the cost matrix C % % E = TESTCOST(A,W,C,LABLIST) % E = TESTCOST(A*W,C,LABLIST) % E = A*W*TESTCOST([],C,LABLIST) % %
www.eeworm.com/read/441245/7672655

m loglc.m

%LOGLC Logistic Linear Classifier % % W = LOGLC(A) % % INPUT % A Dataset % % OUTPUT % W Logistic linear classifier % % DESCRIPTION % Computation of the linear classifier for the dataset