代码搜索:classifiers

找到约 2,305 项符合「classifiers」的源代码

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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/450608/7480572

m fixedcc.m

%FIXEDCC Construction of fixed combiners % % V = FIXEDCC(A,W,TYPE,NAME) % % INPUT % A Dataset % W A set of classifier mappings % TYPE The type of combination rule % NAME The na
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/441245/7672659

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/441245/7672721

m weakc.m

%WEAKC Weak Classifier % % [W,V] = WEAKC(A,ALF,ITER,R) % VC = WEAKC(A,ALF,ITER,R,1) % % INPUT % A Dataset % ALF Fraction of objects to be used for training (def: 0.5) % ITER Numb
www.eeworm.com/read/441245/7672739

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/441245/7673054

m wvotec.m

%WVOTEC Weighted combiner (Adaboost weights) % % W = WVOTEC(A,V) compute weigths and store % W = WVOTEC(V,U) Construct weighted combiner using weights U % % INPUT % A Labeled data
www.eeworm.com/read/441245/7673398

m fixedcc.m

%FIXEDCC Construction of fixed combiners % % V = FIXEDCC(A,W,TYPE,NAME) % % INPUT % A Dataset % W A set of classifier mappings % TYPE The type of combination rule % NAME The na
www.eeworm.com/read/441245/7673410

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/439518/7706976

txt readme.txt

README -------- Directory contains the following files. 1. ADABOOST_te.m 2. ADABOOST_tr.m 3. demo.m 4. likelihood2class.m 5. threshold_te.m 6. threshold_tr.m The aim of the project is to provide