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» Bootstrapping Rule Induction
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ICANN
2003
Springer
14 years 3 months ago
Learning Rule Representations from Boolean Data
We discuss a Probably Approximate Correct (PAC) learning paradigm for Boolean formulas, which we call PAC meditation, where the class of formulas to be learnt is not known in advan...
Bruno Apolloni, Andrea Brega, Dario Malchiodi, Gio...
BTW
1999
Springer
145views Database» more  BTW 1999»
14 years 2 months ago
A Multi-Tier Architecture for High-Performance Data Mining
Data mining has been recognised as an essential element of decision support, which has increasingly become a focus of the database industry. Like all computationally expensive data...
Ralf Rantzau, Holger Schwarz
KDD
1995
ACM
227views Data Mining» more  KDD 1995»
14 years 1 months ago
Applying a Data Miner To Heterogeneous Schema Integration
Anapplication of data miningtechniques to heterogeneous database schemaintegration is introduced. We use attribute-oriented induction to minefor characteristic and classification ...
Son Dao, Brad Perry
JAR
2010
122views more  JAR 2010»
13 years 5 months ago
Partial and Nested Recursive Function Definitions in Higher-order Logic
Based on inductive definitions, we develop a tool that automates the definition of partial recursive functions in higher-order logic (HOL) and provides appropriate proof rules for ...
Alexander Krauss
ICDM
2003
IEEE
158views Data Mining» more  ICDM 2003»
14 years 3 months ago
Identifying Markov Blankets with Decision Tree Induction
The Markov Blanket of a target variable is the minimum conditioning set of variables that makes the target independent of all other variables. Markov Blankets inform feature selec...
Lewis Frey, Douglas H. Fisher, Ioannis Tsamardinos...