代码搜索：classification
找到约 3,679 项符合「classification」的源代码
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www.eeworm.com/read/13871/284693
m demglm2.m
%DEMGLM2 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. Th
www.eeworm.com/read/456693/1604401
py urlparse.py
# Portions Copyright (c) 2005 Nokia Corporation
# A stripped-down version
__all__ = ["urlsplit"]
# A classification of schemes ('' means apply by default)
uses_netloc = ['ftp', 'http', 'gophe
www.eeworm.com/read/251838/4414823
m evaluate_tree_performance.m
function [score,outputs] = evaluate(CPD, fam, data, ns, cnodes)
% Evaluate evaluate the performance of the classification/regression tree on given complete data
% score = evaluate(CPD, fam, data, ns
www.eeworm.com/read/215485/4903784
m evaluate_tree_performance.m
function [score,outputs] = evaluate(CPD, fam, data, ns, cnodes)
% Evaluate evaluate the performance of the classification/regression tree on given complete data
% score = evaluate(CPD, fam, data, ns
www.eeworm.com/read/197905/5091230
m evaluate_tree_performance.m
function [score,outputs] = evaluate(CPD, fam, data, ns, cnodes)
% Evaluate evaluate the performance of the classification/regression tree on given complete data
% score = evaluate(CPD, fam, data, ns
www.eeworm.com/read/175689/5343584
m~ contents.m~
% Algorithms to solve the Generalized Anderson's task.
%
% andrerr - Classification error of the Generalized Anderson's task.
% androrig - Original method to solve the Anderson's task.
% ean
www.eeworm.com/read/346158/3189816
m evaluate_tree_performance.m
function [score,outputs] = evaluate(CPD, fam, data, ns, cnodes)
% Evaluate evaluate the performance of the classification/regression tree on given complete data
% score = evaluate(CPD, fam, data, ns
www.eeworm.com/read/344585/3207786
m demglm1.m
%DEMGLM1 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da
www.eeworm.com/read/344585/3207819
m demglm2.m
%DEMGLM2 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da
www.eeworm.com/read/298327/3867095
cpp s_fpclassifyf.cpp
/* See the import.pl script for potential modifications */
/* Return classification value corresponding to argument.
Copyright (C) 1997, 2000, 2002 Free Software Foundation, Inc.
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