代码搜索：classification
找到约 3,679 项符合「classification」的源代码
代码结果 3,679
www.eeworm.com/read/450608/7480569
m featrank.m
%FEATRANK Feature ranking on individual performance for classification
%
% [I,F] = FEATRANK(A,CRIT,T)
%
% INPUT
% A input dataset
% CRIT string name of a method or untrained mapp
www.eeworm.com/read/442927/7641757
m knnr.m
function [computedOutput, combinedComputedOutput, nearestIndex, knnrMat] = knnr(DS, TS, k)
% knnr: K-nearest neighbor rule for classification
% Usage:
% [computedOutput, combinedComputedOutput, nea
www.eeworm.com/read/441245/7672682
m polyc.m
%POLYC Polynomial Classification
%
% W = polyc(A,CLASSF,N,S)
%
% INPUT
% A Dataset
% CLASSF Untrained classifier (optional; default: FISHERC)
% N Degree of polynomial (optional;
www.eeworm.com/read/441245/7673041
m featseli.m
%FEATSELI Individual feature selection for classification
%
% [W,R] = FEATSELI(A,CRIT,K,T)
%
% INPUT
% A Training dataset
% CRIT Name of the criterion or untrained mapping
% (default:
www.eeworm.com/read/441245/7673395
m featrank.m
%FEATRANK Feature ranking on individual performance for classification
%
% [I,F] = FEATRANK(A,CRIT,T)
%
% INPUT
% A input dataset
% CRIT string name of a method or untrained mapp
www.eeworm.com/read/299459/7850463
m contents.m
% Miscellaneous functions for STPRtoolbox.
%
% adaboost - AdaBoost algorithm.
% adaclass - AdaBoost classifier.
% cerror - Computes classification error.
% crossval - Partions data
www.eeworm.com/read/433439/7929955
m facerecexplanation.m
%FISHERFACES FOR FACE RECOGNITION
%
% We develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression.
% Taking a pattern classification
www.eeworm.com/read/398324/7994138
m getkernel.m
function kernel = getkernel(net)
% GETKERNEL
%
% Accessor method returning the kernel used in a support vector classification
% network.
%
% ker = getkernel(net)
%
% File : @svc/
www.eeworm.com/read/398324/7994249
m getkernel.m
function kernel = getkernel(net)
% GETKERNEL
%
% Accessor method returning the kernel used in a support vector classification
% network.
%
% ker = getkernel(net)
%
% File : @svc/
www.eeworm.com/read/245176/12813178
m getkernel.m
function kernel = getkernel(net)
% GETKERNEL
%
% Accessor method returning the kernel used in a support vector classification
% network.
%
% ker = getkernel(net)
%
% File : @svc/