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/342008/12046885
m polyc.m
%POLYC Polynomial Classification
%
% W = polyc(A,classf,n,s)
%
% Adds polynomial features to the dataset A and runs the untrained
% classifier classf. n is the degree of the polynome (default 1).
www.eeworm.com/read/342008/12046946
m kljlc.m
%KLJLC Linear classifier using KL expansion on the joint data.
%
% W = kljlc(A,n)
%
% Finds the linear discriminant function W for the dataset A
% computing the ldc on a projection of the data on
www.eeworm.com/read/255755/12057884
m parzendc.m
%PARZENDC Parzen density based classifier
%
% [W,H] = PARZENDC(A)
% W = PARZENDC(A,H)
%
% INPUT
% A Dataset
% H Smoothing parameters (optional; default: estimated from A for each class)
www.eeworm.com/read/255755/12057993
m clevals.m
%CLEVALS Classifier evaluation (feature size/learning curve), bootstrap possible
%
% E = CLEVALS(A,CLASSF,FEATSIZE,TRAINSIZES,NREPS,T,FID)
%
% INPUT
% A Training dataset
% CLASSF Cl
www.eeworm.com/read/255755/12058450
m prex_plotc.m
%PREX_PLOTC PRTools example on the dataset scatter and classifier plot
help prex_plotc
echo on
% Generate Higleyman data
A = gendath([100 100]);
% Split the data into the
www.eeworm.com/read/152929/12073841
m baycopt.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Calculate the performance as a classifier
function Gcs = BayCOpt(Gcs,test)
increase = 1;
tp=0; %No True positives
tn=0; %true negatives
fp=0; % false po
www.eeworm.com/read/150905/12249135
m parzendc.m
%PARZENDC Parzen density based classifier
%
% [W,H] = PARZENDC(A)
% W = PARZENDC(A,H)
%
% INPUT
% A Dataset
% H Smoothing parameters (optional; default: estimated from A for each class)
www.eeworm.com/read/150905/12249312
m clevals.m
%CLEVALS Classifier evaluation (feature size/learning curve), bootstrap possible
%
% E = CLEVALS(A,CLASSF,FEATSIZE,TRAINSIZES,NREPS,T,FID)
%
% INPUT
% A Training dataset
% CLASSF Cl
www.eeworm.com/read/150905/12249846
m prex_plotc.m
%PREX_PLOTC PRTools example on the dataset scatter and classifier plot
help prex_plotc
echo on
% Generate Higleyman data
A = gendath([100 100]);
% Split the data into the
www.eeworm.com/read/149739/12353493
m parzendc.m
%PARZENDC Parzen density based classifier
%
% [W,H] = PARZENDC(A)
% W = PARZENDC(A,H)
%
% INPUT
% A Dataset
% H Smoothing parameters (optional; default: estimated from A for each class)