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/280595/10311839
m~ svm2.m~
function model = svm2(data,options)
% SVM2 Learning of binary SVM classifier with L2-soft margin.
%
% Synopsis:
% model = svm2(data)
% model = svm2(data,options)
%
% Description:
% This function le
www.eeworm.com/read/280595/10311859
m svm2.m
function model = svm2(data,options)
% SVM2 Learning of binary SVM classifier with L2-soft margin.
%
% Synopsis:
% model = svm2(data)
% model = svm2(data,options)
%
% Description:
% This function le
www.eeworm.com/read/469416/6976481
m knn.m
function net = knn(nin, nout, k, tr_in, tr_targets)
%KNN Creates a K-nearest-neighbour classifier.
%
% Description
% NET = KNN(NIN, NOUT, K, TR_IN, TR_TARGETS) creates a KNN model NET
% with inpu
www.eeworm.com/read/299984/7140543
m nu_svr.m
%NU_SVR Support Vector Classifier: NU algorithm
%
% [W,J,C] = NU_SVR(A,TYPE,PAR,C,SVR_TYPE,NU_EPS,MC,PD)
%
% INPUT
% A Dataset
% TYPE Type of the kernel (optional; default: 'p')
% PAR K
www.eeworm.com/read/460435/7251019
m nu_svr.m
%NU_SVR Support Vector Classifier: NU algorithm
%
% [W,J,C] = NU_SVR(A,TYPE,PAR,C,SVR_TYPE,NU_EPS,MC,PD)
%
% INPUT
% A Dataset
% TYPE Type of the kernel (optional; default: 'p')
% PAR K
www.eeworm.com/read/458392/7297133
asv svmfit.asv
function [Sigma,Xsup,Alpsup,w0,pos,Time,Crit,SigmaH] = svmfit(Xapp,yapp,Sigma,C,option,pow,verbose)
%SVMFIT Fit SVM Gaussian classifier with adaptive scaling
% [SIGMA,XSUP,ALPSUP,W0] = SVMFIT(XAPP,YA
www.eeworm.com/read/458392/7297134
m svmfit.m
function [Sigma,Xsup,Alpsup,w0,pos,Time,Crit,SigmaH] = svmfit(Xapp,yapp,Sigma,C,option,pow,verbose)
%SVMFIT Fit SVM Gaussian classifier with adaptive scaling
% [SIGMA,XSUP,ALPSUP,W0] = SVMFIT(XAPP,YA
www.eeworm.com/read/441245/7673237
m nu_svr.m
%NU_SVR Support Vector Classifier: NU algorithm
%
% [W,J,C] = NU_SVR(A,TYPE,PAR,C,SVR_TYPE,NU_EPS,MC,PD)
%
% INPUT
% A Dataset
% TYPE Type of the kernel (optional; default: 'p')
% PAR K
www.eeworm.com/read/299459/7850386
m~ svm2.m~
function model = svm2(data,options)
% SVM2 Learning of binary SVM classifier with L2-soft margin.
%
% Synopsis:
% model = svm2(data)
% model = svm2(data,options)
%
% Description:
% This function le
www.eeworm.com/read/299459/7850414
m svm2.m
function model = svm2(data,options)
% SVM2 Learning of binary SVM classifier with L2-soft margin.
%
% Synopsis:
% model = svm2(data)
% model = svm2(data,options)
%
% Description:
% This function le