代码搜索：learner
找到约 833 项符合「learner」的源代码
代码结果 833
www.eeworm.com/read/252978/12252026
java parzen.java
package learner;
public class Parzen implements Classifier {
Data data;
double smoothing = 0;
// ============================================================ Constructor
Parzen(Data d
www.eeworm.com/read/347918/3162036
java learnable.java
package org.joone.engine;
/*
* @author dkern
*/
public interface Learnable {
Learner getLearner();
Monitor getMonitor();
void initLearner();
}
www.eeworm.com/read/252978/12252029
java adaboost.java
package learner;
import java.util.Arrays;
public class Adaboost implements Classifier {
public Data data;
Linear[] strong;
// ========================================================
www.eeworm.com/read/312185/3675477
java incompattexception.java
package jboost.learner;
/** An exception that indicates that an attribute is not what it is
expected to be */
public class IncompAttException extends RuntimeException{
private String messag
www.eeworm.com/read/399996/7816876
asv bagging.asv
function [test_targets] = Bagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Trai
www.eeworm.com/read/399996/7816986
m rocchiobagging.m
function [test_targets] = RocchioBagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets
www.eeworm.com/read/399996/7817088
m bagging.m
function [test_targets] = Bagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Trai
www.eeworm.com/read/399996/7817099
m basebagging.m
function test_targets = BaseBagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Tr
www.eeworm.com/read/245941/12770986
asv bagging.asv
function [test_targets] = Bagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Trai
www.eeworm.com/read/245941/12771097
m rocchiobagging.m
function [test_targets] = RocchioBagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets