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/460435/7250462
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/460435/7251005
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/460435/7251252
m prex_plotc.m
%PREX_PLOTC PRTools example on the dataset scatter and classifier plot
help prex_plotc
n = prprogress;
prprogress off
echo on
% Generate Higleyman data
A = gendath([100 100]);
www.eeworm.com/read/451308/7467547
java bayesresult.java
package ir.classifiers;
import java.util.*;
/**
* An object to hold the result of training a NaiveBayes classifier.
* Stores the class priors and the counts of features in each class.
*
* @autho
www.eeworm.com/read/450608/7480067
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 parameter
www.eeworm.com/read/450608/7480106
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/450608/7480108
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/450608/7480427
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/442927/7641745
m crossceval.m
function [output, recogRate]=crosscEval(DS, coef)
%crosscEval: Evaluation of cross classifier
% Usage: [output, recogRate]=crosscEval(DS, coef)
% Roger Jang, 20041106
xCut=coef(1);
yCut=coef(
www.eeworm.com/read/441245/7672598
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