代码搜索：evaluate
找到约 3,619 项符合「evaluate」的源代码
代码结果 3,619
www.eeworm.com/read/218623/14911972
m evaluate_by_inst_choice.m
function [acc, ncorrect] = evaluate_by_inst_choice(bags, labels)
nbag = length(bags);
ninst = 0;
for i=1:nbag, ninst = ninst + size(bags(i).instance, 1); end;
if (ninst ~= length(labels)) || (ni
www.eeworm.com/read/218623/14912104
m mil_inst_evaluate.m
function [acc, ncorrect] = MIL_inst_evaluate(bags, labels)
nbag = length(bags);
ninst = 0;
for i=1:nbag, ninst = ninst + size(bags(i).instance, 1); end;
if (ninst ~= length(labels)) || (ninst ==
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/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/292984/3936057
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/292964/3937205
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