代码搜索：Voting

找到约 208 项符合「Voting」的源代码

代码结果 208
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py accuracy5.py

# Category: evaluation # Description: Estimation of accuracy by cross validation. Demonstration of use for different learners. # Uses: voting.tab # Classes: MakeRandomIndicesCV # Ref
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www.eeworm.com/read/429426/1948724

py domain10.py

# Description: A simple implementation of wrapper feature subset selection # Category: modelling # Uses: voting # Classes: Domain, orngTest.crossValidation # Referenced: domain.htm
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www.eeworm.com/read/429426/1948671

py statexamples.py

import orange, orngTest, orngTree learners = [orange.BayesLearner(name = "bayes"), orngTree.TreeLearner(name="tree"), orange.MajorityLearner(name="majrty")] voting = or
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www.eeworm.com/read/415313/11076983

m mcwithvoting.m

% MCWithVoting: implementation for meta-classification with majority voting % % Parameters: % classifier: base classifier % para: parameters % 1. PosRatio: ratio of positive examples after s
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www.eeworm.com/read/241991/4556852

java votinglistener.java

package org.jgroups.blocks; /** * Implemetations of this interface are able to participate in voting process. * * @author Roman Rokytskyy (rrokytskyy@acm.org) */ public interface VotingListener
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www.eeworm.com/read/429426/1948666

py tuning1.py

import orange, orngTree, orngWrap, orngStat learner = orngTree.TreeLearner() data = orange.ExampleTable("voting") tuner = orngWrap.Tune1Parameter(object=learner,
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www.eeworm.com/read/429426/1948676

py fss1.py

# Description: Ranking and selection of best N attributes # Category: preprocessing # Uses: voting # Referenced: orngFSS.htm # Classes: orngFSS.attMeasure, orngFSS.bestNAtts impo
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www.eeworm.com/read/429426/1948680

py fss2.py

# Description: Ranking of attributes with two different measures (Relief and gain ratio) # Category: preprocessing # Uses: voting.tab # Referenced: orngFSS.htm # Classes: orngFSS.at
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www.eeworm.com/read/429426/1948693

py fss3.py

# Description: Compares naive Bayes with and withouth feature subset selection # Category: preprocessing # Uses: voting.tab # Referenced: orngFSS.htm # Classes: orngFSS.attMeasure,
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www.eeworm.com/read/429426/1948715

py accuracy2.py

# Description: Set a number of learners, for each build a classifier from the data and determine classification accuracy # Category: evaluation # Uses: voting.tab # Referenced: c_perform
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