Rule Induction and Instance-Based Learning: A Unified Approach

Rule Induction and Instance-Based Learning: A Unified Approach (1995)

by Pedro Domingos

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Datum	Value	Source
TITLE	Rule Induction and Instance-Based Learning: A Unified Approach	user correction - Legacy Corrections
AUTHOR NAME	Pedro Domingos	SVM HeaderParse 0.1
AUTHOR AFFIL	Department of Information and Computer Science; University of California, Irvine	SVM HeaderParse 0.2
AUTHOR ADDR	Irvine, California 92717, U.S.A.	SVM HeaderParse 0.1
ABSTRACT	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 specific-to-general fashion, starting with one rule per training example, and avoids some of the difficulties of separate-andconquer approaches by evaluating each proposed induction step globally, i.e., through an efficient procedure that is equivalent to checking the accuracy of the rule set as a whole on every training example. Classification is performed using a best-match strategy, and reduces to nearest-neighbor if all generalizations of instances were rejected. An extensive empirical study shows that RISE consistently achieves higher accuracies than state-of-the-art representatives of its "parent" paradigms (PEBLS and CN2), and also outperforms a decision-tree learner (C4.5) in 13 out of 15 test domains (in 10 with 95% confidence). 1 Introduction Several well-developed approaches to indu...	user correction - Legacy Corrections
YEAR	1995	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	1226--1232	INFERENCE
CITATIONS	28 found	ParsCit 1.0