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/466591/7029554
asv cerror.asv
function error=cerror(y1,y2,label)
% CERROR Computes classification error.
%
% Synopsis:
% error = cerror(y1,y2)
% error = cerror(y1,y2,label)
%
% Description:
% error = cerror(y1,y2) returns clas
www.eeworm.com/read/299984/7139978
m perlc.m
% PERLC - Train a linear perceptron classifier
%
% W = PERLC(A)
% W = PERLC(A,MAXITER,ETA,W_INI,TYPE)
%
% INPUT
% A Training dataset
% MAXITER Maximum number of iterations (default 10
www.eeworm.com/read/299984/7140683
m logdens.m
%LOGDENS Force density based classifiers to use log-densities
%
% V = LOGDENS(W)
% V = W*LOGDENS
%
% INPUT
% W Density based trained classifier
%
% OUTPUT
% V Log-density based tr
www.eeworm.com/read/460435/7250453
m perlc.m
% PERLC - Train a linear perceptron classifier
%
% W = PERLC(A)
% W = PERLC(A,MAXITER,ETA,W_INI,TYPE)
%
% INPUT
% A Training dataset
% MAXITER Maximum number of iterations (default 10
www.eeworm.com/read/460435/7251159
m logdens.m
%LOGDENS Force density based classifiers to use log-densities
%
% V = LOGDENS(W)
% V = W*LOGDENS
%
% INPUT
% W Density based trained classifier
%
% OUTPUT
% V Log-density based tr
www.eeworm.com/read/451547/7461930
m contents.m
% Data Description Toolbox
% Version 1.6.3 3-Jun-2008
%
%Dataset construction
%--------------------
%isocset true if dataset is one-class dataset
%gendatoc generate a one-class dataset fr
www.eeworm.com/read/450608/7480559
m logdens.m
%LOGDENS Force density based classifiers to use log-densities
%
% V = LOGDENS(W)
% V = W*LOGDENS
%
% INPUT
% W Density based trained classifier
%
% OUTPUT
% V Log-density based tr
www.eeworm.com/read/450608/7480587
m fisherc.m
%FISHERC Fisher's Least Square Linear Classifier
%
% W = FISHERC(A)
%
% INPUT
% A Dataset
%
% OUTPUT
% W Fisher's linear classifier
%
% DESCRIPTION
% Finds the linear discriminant functio
www.eeworm.com/read/441245/7672658
m perlc.m
% PERLC - Train a linear perceptron classifier
%
% W = PERLC(A)
% W = PERLC(A,MAXITER,ETA,W_INI,TYPE)
%
% INPUT
% A Training dataset
% MAXITER Maximum number of iterations (default 10
www.eeworm.com/read/441245/7673379
m logdens.m
%LOGDENS Force density based classifiers to use log-densities
%
% V = LOGDENS(W)
% V = W*LOGDENS
%
% INPUT
% W Density based trained classifier
%
% OUTPUT
% V Log-density based tr