pool-based learning via weighted information gain measurements
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Pool-based learning via Weighted Information Gain Measurements. Rafael Augusto Ferreira do Carmo [email protected] Daniel Pinto Coutinho [email protected] Jerffeson Teixeira de Souza [email protected] Universidade Estadual do Ceará - PowerPoint PPT PresentationTRANSCRIPT
Pool-based learning via Weighted Information Gain Measurements
Pool-based learning via Weighted Information Gain MeasurementsRafael Augusto Ferreira do Carmo [email protected] Pinto Coutinho [email protected] Teixeira de Souza [email protected]
Universidade Estadual do CearFortaleza - Brazil
1IntroductionActive learning scenarioBinary classification problems
Pool of unlabeled examples
No prior information about class distribution
One labeled example as seed for learning
2The TaskSelect the as few informative examples as possible
Minimize the classification costs
Maximize the quality of the model
3The AlgorithmWhat if this example is positive?
What if this example is negative?
Information Gain Ratio
Weight features
4The Algorithm
5Results Datasets
6Results - RankingDatasetExperimentScore (AUC)Global Score (ALC)RankAverifA0.7547350.35059310BexpB0.6340620.19604711EexpE0.6825210.20259114FexpF0.7095960.27323016
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