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Probabilistic rule induction with the LERS data mining system

https://doi.org/10.1002/int.20482

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/11427834_10openalex-snapshot

Rough Sets and Bayes Factor

inferredcites →https://doi.org/10.1007/978-3-540-72458-2_1openalex-snapshot

Decision-Theoretic Rough Set Models

inferredcites →https://doi.org/10.1007/978-3-540-88425-5_21openalex-snapshot

A Comparison of the LERS Classification System and Rule Management in PRSM

inferredcites →https://doi.org/10.1007/978-3-642-02962-2_81openalex-snapshot

Three-Way Decision: An Interpretation of Rules in Rough Set Theory

inferredcites →https://doi.org/10.1007/bf00437317openalex-snapshot

Knowledge acquisition under uncertainty ? a rough set approach

inferredcites →https://doi.org/10.1016/0020-7373(92)90093-zopenalex-snapshot

Applications and extensions of OWA aggregations

inferredcites →https://doi.org/10.1016/0022-0000(93)90048-2openalex-snapshot

Variable precision rough set model

inferredcites →https://doi.org/10.1016/0094-114x(91)90075-fopenalex-snapshot

Machine learning—Paradigms and methods

inferredcites →https://doi.org/10.1016/j.ijar.2007.05.018openalex-snapshot

Parameterized rough set model using rough membership and Bayesian confirmation measures

inferredcites →https://doi.org/10.1016/j.ins.2008.06.013openalex-snapshot

Stochastic dominance-based rough set model for ordinal classification

inferredcites →https://doi.org/10.1016/j.ins.2009.09.021openalex-snapshot

Three-way decisions with probabilistic rough sets

inferredcites →https://doi.org/10.1016/s0020-7373(88)80032-4openalex-snapshot

Rough sets: probabilistic versus deterministic approach

inferredcites →https://doi.org/10.1023/a:1007329424533openalex-snapshot

Pruning Algorithms for Rule Learning

inferredcites →https://doi.org/10.1109/mex.1987.4307100openalex-snapshot

Induction: Processes of Inference, Learning, and Discovery

inferredcites →https://doi.org/10.1111/j.1467-8640.1995.tb00040.xopenalex-snapshot

PRIMEROSE: PROBABILISTIC RULE INDUCTION METHOD BASED ON ROUGH SETS AND RESAMPLING METHODS

inferredcites →https://doi.org/10.3233/fi-1997-3113openalex-snapshot

A New Version of the Rule Induction System LERS

inferredcites →https://doi.org/10.4018/978-1-59140-051-6.ch006openalex-snapshot

Data Mining Based on Rough Sets

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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On Interpreting Three-Way Decisions through Two-Way Decisions

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Complexity of Rule Sets Induced from Incomplete Data Sets Using Global Probabilistic Approximations

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A Rough Set Approach to Incomplete Data

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Rough Sets and Three-Way Decisions

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Three-Way Decisions Based on Intuitionistic Fuzzy Sets

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An Empirical Comparison of Rule Sets Induced by LERS and Probabilistic Rough Classification

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An Empirical Comparison of Rule Sets Induced by LERS and Probabilistic Rough Classification

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An Outline of a Theory of Three-Way Decisions

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Comparison of Two Models of Probabilistic Rough Sets

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Granular Computing and Sequential Three-Way Decisions

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Generalizations of Approximations

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Rule Induction from Rough Approximations

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The Application of Rough Sets Theory to Design of Weld Defect Classifiers

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RETRACTED: Three-way decisions based on neutrosophic sets and AHP-QFD framework for supplier selection problem

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Synergies between machine learning and reasoning - An introduction by the Kay R. Amel group

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Mining incomplete data with singleton, subset and concept probabilistic approximations

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A new approach of optimal scale selection to multi-scale decision tables

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A comparison of positive, boundary, and possible rules using the MLEM2 rule induction algorithm

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A Novel Deep Web Data Mining Algorithm based on Multi-Agent Information System and Collaborative Correlation Rule

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Homomorphisms Between Covering Approximation Spaces

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