Classification of MMPI profiles of patients with mental disorders: experiments with attribute reduction and extension

Authors:
Jerzy Gomuła;Krzysztof Pancerz;Jarosław Szkoła
Affiliations:
The Andropause Institute, Medan Foundation, Warsaw, Poland and Cardinal Stefan Wyszyński University in Warsaw, Poland;Institute of Biomedical Informatics, University of Information Technology and Management in Rzeszów, Poland;Institute of Biomedical Informatics, University of Information Technology and Management in Rzeszów, Poland
Venue:
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Year:
2010

Citing 7
Cited 3

A new version of the rule induction system LERS

Fundamenta Informaticae
Rough set algorithms in classification problem

Rough set methods and applications
MMPI: Clinical Assessment and Automated Interpretation

MMPI: Clinical Assessment and Automated Interpretation
Induction of Decision Trees

Machine Learning
Covering with Reducts - A Fast Algorithm for Rule Generation

RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
The rough set exploration system

Transactions on Rough Sets III

Experiments with hybridization and optimization of the rules knowledge base for classification of MMPI profiles

ICDM'11 Proceedings of the 11th international conference on Advances in data mining: applications and theoretical aspects
Ant based clustering of MMPI data: an experimental study

RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Decision rules development using set of generic operations approach

ICDM'12 Proceedings of the 12th Industrial conference on Advances in Data Mining: applications and theoretical aspects

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the research presented in the paper we try to find efficient methods for classification of MMPI profiles of patients with mental disorders. Each profile is described by a set of values of thirteen attributes (scales). Patients can be classified into twenty categories concerning nosological types. It is possible to improve classification accuracy by reduction or extension of the number of attributes with relation to the original data table. We test several techniques of reduction and extension. Experiments show that the proposed attribute extension approach improves classification accuracy, especially in the case of discretized data.