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/214923/15082968
m code.m
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/213492/15133231
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/213492/15133233
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/213492/15133684
m contents.m
% Miscellaneous functions for STPRtoolbox.
%
% adaboost - AdaBoost algorithm.
% adaclass - AdaBoost classifier.
% cerror - Computes classification error.
% crossval - Partions data
www.eeworm.com/read/213240/15139971
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/213240/15139990
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/211316/15183052
txt see5sam.txt
To run See5Sam.exe from a command prompt window:
* Make sure that you have run See5 on your application to construct
the kind of classifier that you want to use.
* Put See5Sam.exe in the
www.eeworm.com/read/293183/8310584
m crossval.m
%CROSSVAL Crossvalidation, classifier error and stability
%
% [e,s] = crossval(classf,A,n)
%
% Crossvalidation estimation of the error and the instability of the
% classifier classf using the data
www.eeworm.com/read/293183/8310738
m setreject.m
%SETREJECT Set classifier reject value
function w = setreject(w,r)
w.r = r;
return
www.eeworm.com/read/172172/9722059
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay