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Abstract: We present the RIAC (Rule Induction through Approximate Classification) method for inducing rules from examples, based on the theory of rough sets. Imprecise data are generalized using a rough-sets based approximation technique. Positive, boundary and negative regions of the target concept are defined using statistical information. Then, if the concept is learnable, superfluous attributes are eliminated and rules are generated. Each classification rule generated by the RIAC algorithm is tagged... (Update)
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...results belong to the best reported so far. PVM, Cart, MLP and Bayes results are taken from [15] C MLP2LN from [16] RIAC and C4.5 from [18] and FSM [19] are our own. Unfortunately we have only a few results of the the leave one out tests to compare with. k NN result for...
.... for diabetes dataset Method Accuracy Reference 3 NN 96.7 Karol Grudzi nski (our group) MLP BP 96.0 Sigillito [7] C4.5 94.9 Hamilton [8] FSM 92.8 Rafal Adamczak (our group) 9] SSV Tree 92.0 this paper DB CART 91.3 Shang, Breiman [10] CART 88.9 Shang, Breiman [10] Table 2:...
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BibTeX entry: (Update)
H.J. Hamilton, N. Shan, N. Cercone, RIAC: a rule induction algorithm based on approximate classification, Tech. Rep. CS 96-06, Regina University 1996 http://citeseer.ist.psu.edu/hamilton96riac.html More
@misc{ hamilton96riac,
author = "H. Hamilton and N. Shan and N. Cercone",
title = "RIAC: a rule induction algorithm based on approximate classification",
text = "H.J. Hamilton, N. Shan, N. Cercone, RIAC: a rule induction algorithm based
on approximate classification, Tech. Rep. CS 96-06, Regina University 1996",
year = "1996",
url = "citeseer.ist.psu.edu/hamilton96riac.html" }
Citations (may not include all citations):2177 Programs for Machine Learning (context) - Quinlan - 1992
1359 Induction of Decision Trees (context) - Quinlan - 1986
1262 Classification and Regression Trees (context) - Breiman, Friedman et al. - 1984
392 A Theory and Methodology of Inductive Learning (context) - Michalski - 1983
220 Rough Sets: Theoretical Aspects of Reasoning About Data (context) - Pawlak - 1991
180 The CN2 Induction Algorithm (context) - Clark, Niblett - 1989
160 Knowledge Discovery in Databases (context) - Piatetsky-Shapiro, Frawley - 1991
111 The Feature Selection Problem: Traditional Methods and a New.. (context) - Kira, Rendell - 1992
99 Concept Learning and the Problem of Small Disjuncts (context) - Holte, Acker et al. - 1989
75 The Multi-Purpose Incremental Learning System AQ15 and Its T.. (context) - Michalski, Mozetic et al. - 1986
44 Variable Precision Rough Set Model (context) - Ziarko - 1993
31 An SE-Tree Based Characterization of the Induction Problem - Rymon - 1993
29 Rule Induction and Instance-Based Learning: A Unified Approa.. - Domingos - 1995
21 Improved Decision Trees: A Generalized Version of ID3 (context) - Cheng, Fayyad et al. - 1988
20 SKICAT: A Machine Learning System for Automated Cataloging o.. (context) - Fayyad, Weir et al. - 1993
17 Intelligent Decision Support: Handbook of Applications and A.. (context) - Slowinski - 1992
12 Rough Classification (context) - Pawlak - 1984
8 Branching on Attribute Values in Decision Tree Generation (context) - Fayyad - 1994
5 Discovery, Analysis, and Presentation of Strong Rules (context) - Piatetsky-Shapiro - 1991
4 Knowledge Acquisition under Uncertainty: A Rough Set Approac.. (context) - Grzymala-Busse - 1988
3 Noise Handling with Extension Matrices - Wu, Krisar et al. - 1995
2 Incremental Learning of Production Rules from Examples under.. (context) - Chan - 1991
1 The MONK's Problems: A Performance Comparision of Different .. (context) - Thrun - 1991
1 On Changing Continuous Attributes into Order Discrete Attrib.. (context) - Catlett - 1991
1 GRG: Knowledge Discovery Using Information Generalization, I.. (context) - Shan, Hamilton et al. - 1995
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