代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/299984/7139963
m qdc.m
%QDC Quadratic Bayes Normal Classifier (Bayes-Normal-2)
%
% [W,R,S,M] = QDC(A,R,S,M)
% W = A*QDC([],R,S)
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/460435/7250438
m qdc.m
%QDC Quadratic Bayes Normal Classifier (Bayes-Normal-2)
%
% [W,R,S,M] = QDC(A,R,S,M)
% W = A*QDC([],R,S)
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/441245/7672642
m qdc.m
%QDC Quadratic Bayes Normal Classifier (Bayes-Normal-2)
%
% [W,R,S,M] = QDC(A,R,S,M)
% W = A*QDC([],R,S)
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/299459/7850370
m~ evalsvm.m~
function [best_model,Errors] = evalsvm(arg1,arg2,arg3)
% EVALSVM Trains and evaluates Support Vector Machines classifier.
%
% Synopsis:
% [model,Errors] = evalsvm(data,options)
% [model,Errors] = ev
www.eeworm.com/read/299459/7850383
m evalsvm.m
function [best_model,Errors] = evalsvm(arg1,arg2,arg3)
% EVALSVM Trains and evaluates Support Vector Machines classifier.
%
% Synopsis:
% [model,Errors] = evalsvm(data,options)
% [model,Errors] = ev
www.eeworm.com/read/397111/8067070
m lpdd.m
function W = lpdd(x,nu,s,dtype,par)
%LPDD Linear programming distance data description
%
% W = LPDD(X,NU,S,DTYPE,P)
%
% One-class classifier put into a linear programming framework. From
% th
www.eeworm.com/read/397102/8068005
m knn_map.m
%KNN_MAP Map a dataset on a K-NN based classifier
%
% F = knn_map(A,W)
%
% Maps the dataset A by the K-NN classfier W on the [0,1] interval
% for each of the classes W is trained on. The posterior
www.eeworm.com/read/312163/13617427
m evalsvm.m
function [best_model,Errors] = evalsvm(arg1,arg2,arg3)
% EVALSVM Trains and evaluates Support Vector Machines classifier.
%
% Synopsis:
% [model,Errors] = evalsvm(data,options)
% [model,Errors] = ev
www.eeworm.com/read/493294/6399887
m lpdd.m
function W = lpdd(x,nu,s,dtype,par)
%LPDD Linear programming distance data description
%
% W = LPDD(X,NU,S,DTYPE,P)
%
% One-class classifier put into a linear programming framework. From
% th
www.eeworm.com/read/400577/11572606
m qdc.m
%QDC Quadratic Bayes Normal Classifier (Bayes-Normal-2)
%
% [W,R,S,M] = QDC(A,R,S,M)
% W = A*QDC([],R,S)
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0