Unifying instance-based and rule-based induction
نویسندگان
چکیده
منابع مشابه
Unifying Instance - Based and Rule - Based Induction
Several well-developed approaches to inductive learning now exist, but each has speci c limitations that are hard to overcome. Multi-strategy learning attempts to tackle this problem by combining multiple methods in one algorithm. This article describes a uni cation of two widely-used empirical approaches: rule induction and instance-based learning. In the new algorithm, instances are treated a...
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This paper presents a new approach to inductive learning that combines aspects of instancebased learning and rule induction in a single simple algorithm. The RISE system searches for rules in a speci c-to-general fashion, starting with one rule per training example, and avoids some of the di culties of separate-andconquer approaches by evaluating each proposed induction step globally, i.e., thr...
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Obtaining large volumes of inference knowledge, such as entailment rules, has become a major factor in achieving robust semantic processing. While there has been substantial research on learning algorithms for such knowledge, their evaluation methodology has been problematic, hindering further research. We propose a novel evaluation methodology for entailment rules which explicitly addresses th...
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In this paper, a new rule induction method by using EDA with instance-subpopulations is proposed. The proposed method introduces a notion of instance-subpopulation, where a set of individuals matching a training instance. Then, EDA procedure is separately carried out for each instance-subpopulation. Individuals generated by each EDA procedure are merged to constitute the population at the next ...
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A new prepruning technique for rule induction is presented which applies instance reduction before rule induction. An empirical evaluation records the predictive accuracy and size of rule-sets generated from 24 datasets from the UCI Machine Learning Repository. Three instance reduction algorithms (Edited Nearest Neighbour, AllKnn and DROP5) are compared. Each one is used to reduce the size of t...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 1996
ISSN: 0885-6125,1573-0565
DOI: 10.1007/bf00058656