代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/431675/8662256
m clevalf.m
%CLEVALF Classifier evaluation (feature size curve)
%
% [e,s] = clevalf(classf,A,featsizes,learnsize,n,T,print)
%
% Generates at random for all feature sizes stored in featsizes
% training sets of
www.eeworm.com/read/431675/8662297
m emclust.m
%EMCLUST Expectation - Maximization clustering
%
% [D,V] = emclust(A,W,n)
%
% The untrained classifier W is used to update an initially labelled
% dataset A by the following two steps:
% 1. train W by
www.eeworm.com/read/386050/8767251
m spatm.m
%SPATM Augment image dataset with spatial label information
%
% E = SPATM(D,S)
% E = D*SPATM([],S)
%
% INPUT
% D image dataset classified by a classifier
% S smoothing paramet
www.eeworm.com/read/386050/8767412
m averagec.m
%AVERAGEC Combining of linear classifiers by averaging coefficients
%
% W = AVERAGEC(V)
% W = V*AVERAGEC
%
% INPUT
% V A set of affine base classifiers.
%
% OUTPUT
% W Combined classifier.
%
%
www.eeworm.com/read/386050/8767420
m rbnc.m
%RBNC Radial basis function neural network classifier
%
% W = RBNC(A,UNITS)
%
% INPUT
% A Dataset
% UNITS Number of RBF units in hidden layer
%
% OUTPUT
% W Radial basis neural n
www.eeworm.com/read/386050/8768901
m costm.m
%COSTM Cost mapping, classification using costs
%
% Y = COSTM(X,C,LABLIST)
% W = COSTM([],C,LABLIST)
%
% DESCRIPTION
% Maps the classifier output X (assumed to be posterior probability
% estimate
www.eeworm.com/read/428849/8834592
m psvm.m
function varargout=psvm(model,options)
% PSVM Plots decision boundary of binary SVM classifier.
%
% Synopsis:
% h = psvm(...)
% psvm(model)
% psvm(model,options)
%
% Description:
% This function s
www.eeworm.com/read/428849/8834864
m perceptron.m
function model=perceptron(data,options,init_model)
% PERCEPTRON Perceptron algorithm to train binary linear classifier.
%
% Synopsis:
% model = perceptron(data)
% model = perceptron(data,options)
%
www.eeworm.com/read/426679/9004388
m mnfpclassifier.m
% Modified Nearest Feature Plane Classifier-MNFP
function [MNFPCrate]=MNFPclassifier(features,test_features,trnum,tenum,classnum,K)
% features the matrix that training samples projected on f
www.eeworm.com/read/426679/9004391
m mnflclassifier.m
% Modified Nearest Feature Line Classifier-MNFL
function [MNFLCrate]=MNFLclassifier(features,test_features,trnum,tenum,classnum,K)
% features the matrix that training samples projected on fe