代码搜索：Supervised
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www.eeworm.com/read/130490/14190022
readme
Select - Supervised Learning Email Classification Tool
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Copyright (C) 2001-2002, 2003 Mikael Ylikoski
{ Introduction }
Select is a tool for
www.eeworm.com/read/438849/7106020
java coforest.java
package coforest;
/**
* Description: CoForest is a semi-supervised algorithm, which exploits the power of ensemble learning and available
* large amount of unlabeled data to produc
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xml introduction.xml
Introduction
Select is a tool for performing and evaluating email classification using supervised learning methods with in
www.eeworm.com/read/307651/13718047
m dosom.m
% doSom: Supervised classification using Self-Organizing Map (SOM is
% actually an unsupervised clustering technique. )
%
% [C] = doSom(data, proto, protoClass)
%
% Input and output argument
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xml natural.xml
Natural Selection
Natural Selection
Naturally Supervised Learning Email Classification Tool Interface Outline
is a simpl
www.eeworm.com/read/393794/8262994
m sda.m
function [eigvector, eigvalue, elapse] = SDA(gnd,fea,LabelIdx,UnlabelIdx,options)
% SDA: Semi-supervised Discriminant Analysis
%
% [eigvector, eigvalue, elapse] = SDA(gnd,feaLabel,feaUnlabel,
www.eeworm.com/read/170469/9805427
java schema.java
package shared;
import java.util.*;
import java.lang.*;
import java.io.*;
/** Schema defines the attribute information. Most effort was directed at labelled
* instances for supervised learning
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java schema.java
package shared;
import java.util.*;
import java.lang.*;
import java.io.*;
/** Schema defines the attribute information. Most effort was directed at labelled
* instances for supervised learning
www.eeworm.com/read/161460/10407330
java schema.java
package shared;
import java.util.*;
import java.lang.*;
import java.io.*;
/** Schema defines the attribute information. Most effort was directed at labelled
* instances for supervised learning
www.eeworm.com/read/424119/10490904
c srng_model.c
/*
Supervised Relevance Natural Gaz classification algorithm.
Usage
------
[Wproto_est , yproto_est , E_SRNG] = srng_model(Xtrain , ytrain , [Wproto] , [yproto] , [lambda] , [optio