Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks.

Stahl, F. and Bramer, M., 2012. Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks. Knowledge-Based Systems, 35, 49 - 63 .

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DOI: 10.1016/j.knosys.2012.04.014

Abstract

In order to gain knowledge from large databases, scalable data mining technologies are needed. Data are captured on a large scale and thus databases are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.

Item Type:Article
ISSN:0950-7051
Subjects:Technology > Engineering > Electrical and Electronic Engineering
Group:School of Design, Engineering & Computing
ID Code:20512
Deposited By:Unnamed user with email symplectic@symplectic
Deposited On:16 Nov 2012 16:24
Last Modified:21 Nov 2012 14:17

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