代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
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www.eeworm.com/read/374698/9388953
asv code.asv
function [nsignals, codebook, oldcodebook, scheme] = code(signals,codetype,codetype_args,oldcodebook,fctdist,fctdist_args)
% Encode and decode a multi-class classification task into multiple binary cl
www.eeworm.com/read/362246/10009277
m~ bayesdf.m~
function quad_model=bayesdf(model)
% BAYESDF Computes decision boundary of Bayesian classifier.
%
% Synopsis:
% quad_model = bayesdf(model)
%
% Description:
% This function computes parameter
www.eeworm.com/read/362246/10009280
m bayesdf.m
function quad_model=bayesdf(model)
% BAYESDF Computes decision boundary of Bayesian classifier.
%
% Synopsis:
% quad_model = bayesdf(model)
%
% Description:
% This function computes parameter
www.eeworm.com/read/362246/10010125
m contents.m
% Miscellaneous functions for STPRtoolbox.
%
% adaboost - AdaBoost algorithm.
% adaclass - AdaBoost classifier.
% cerror - Computes classification error.
% crossval - Partions data
www.eeworm.com/read/360995/10069908
m stump_dd.m
%STUMP_DD Threshold one dim. one-class classifier
%
% W = STUMP_DD(A,FRACREJ,DIM)
%
% Put a threshold on one of the feature dimensions DIM of dataset A. The
% threshold is put such that a frac
www.eeworm.com/read/360995/10069914
m dd_setfn.m
function v = dd_setfn(w,a,thr)
%DD_SETFN Set the threshold to a specific FN rate
%
% V = DD_SETFN(W,A,THR)
%
% The data of classifier W is copied to classifier V, only the
% threshold value is cha
www.eeworm.com/read/360995/10069940
m random_dd.m
%RANDOM_DD Random one-class classifier
%
% W = RANDOM_DD(A,FRACREJ)
%
% This is the trivial one-class classifier, randomly assigning labels
% and rejecting FRACREJ of the data objects. This pr
www.eeworm.com/read/281002/10273015
nb2 subset.nb2
/*----------------------------------------------------------------------
domains
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dom(x) = ZZ [0, 6];
dom(y) = ZZ [0, 8];
dom(
www.eeworm.com/read/281002/10273046
fbc test.fbc
/*----------------------------------------------------------------------
domains
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dom(x) = IR;
dom(y) = IR;
dom(class) = { a,