Titlebook: Machine Learning: ECML 2001; 12th European Confer Luc Raedt,Peter Flach Conference proceedings 2001 Springer-Verlag Berlin Heidelberg 2001

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書目名稱Machine Learning: ECML 2001影響因子(影響力)




書目名稱Machine Learning: ECML 2001影響因子(影響力)學(xué)科排名




書目名稱Machine Learning: ECML 2001網(wǎng)絡(luò)公開度




書目名稱Machine Learning: ECML 2001網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Machine Learning: ECML 2001被引頻次




書目名稱Machine Learning: ECML 2001被引頻次學(xué)科排名




書目名稱Machine Learning: ECML 2001年度引用




書目名稱Machine Learning: ECML 2001年度引用學(xué)科排名




書目名稱Machine Learning: ECML 2001讀者反饋




書目名稱Machine Learning: ECML 2001讀者反饋學(xué)科排名

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0302-9743 ment learning, sequence prediction, sequential decisions, classification learning, sampling, and semi-supervised learning.978-3-540-42536-6978-3-540-44795-5Series ISSN 0302-9743 Series E-ISSN 1611-3349

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A Simple Approach to Ordinal Classificationh a decision tree learner we show that it outperforms the naive approach, which treats the class values as an unordered set. Compared to special-purpose algorithms for ordinal classification our method has the advantage that it can be applied without any modification to the underlying learning scheme.

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Using Subclasses to Improve Classification Learningine”, “faulty lights”, etc..This hypothesis was corroborated using a number of ‘real-world’ multi-class data sets from the UCIMLrepository. Our empirical studies demonstrate the usefulness of the proposed research methodology using artificial data sets as an important methodological complement to using real-world datasets.

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Conference proceedings 2001 2001..The 50 revised full papers presented together with four invited contributions were carefully reviewed and selected from a total of 140 submissions. Among the topics covered are classifier systems, naive-Bayes classification, rule learning, decision tree-based classification, Web mining, equat

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Learning While Exploring: Bridging the Gaps in the Eligibility Tracesl reward equal to its estimated cost of making the exploring move. This modification is compatible with existing exploration strategies, and is seen to work well when applied to a simple grid-world problem, even when always exploring completely at random.

NOVA

An Axiomatic Approach to Feature Term Generalizations of the definition is given on the basis of the axiomatic foundation. An operational definition of the least general generalization of clauses based on Ψ-terms is also shown as a realization of the axiomatic definition.

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