A ROUGH SET BASED FUZZY INFERENCE SYSTEM
FOR MINING TEMPORAL MEDICAL DATABASES
U Keerthika1 R Sethukkarasi2 and A Kannan3
1 PG Student, Department of Computer Science and Engineering, R.M.K. Engineering
College, Kavaraipettai, Tamil Nadu, India
keerthi.umapathy@gmail.com
2 Research Scholar, Department of Information Science and Technology, Anna
University, Chennai, Tamil Nadu, India
sethumaaran@yahoo.co.in
3 Professor, Department of Information Science and Technology, Anna University,
Chennai, Tamil Nadu, India
kannan@annauniv.edu
ABSTRACT
The main objective of this research work is to construct a Fuzzy Temporal Rule Based Classifier that uses
fuzzy rough set and temporal logic in order to mine temporal patterns in medical databases. The lower
approximation concepts and fuzzy decision table with the fuzzy features are used to obtain fuzzy decision
classes for building the classifier. The goals are pre-processing for feature selection, construction of
classifier, and rule induction based on increment rough set approach. The features are selected using
Hybrid Genetic Algorithm. Moreover the elementary sets are obtained from lower approximations are
categorized into the decision classes. Based on the decision classes a discernibility vector is constructed to
define the temporal consistency degree among the objects. Now the Rule Based Classifier is transformed
into a temporal rule based fuzzy inference system by incorporating the Allen’s temporal algebra to induce
rules. It is proposed to use incremental rough set to update rule induction in dynamic databases. Ultimately
these rules are categorized as rules with range values to perform prediction effectively. The efficiency of
the approach is compared with other classifiers in order to assess the accuracy of the fuzzy temporal rule
based classifier. Experiments have been carried out on the diabetic dataset and the simulation results
obtained prove that the proposed temporal rule-based classifier on clinical diabetic dataset stays as an
evidence for predicting the severity of the disease and precision in decision support system.
KEYWORDS
Fuzzy Rough Sets, Lower approximations, Rule Based Classifier, Allen’s Temporal Algebra
ORIGINAL SOURCE URL : http://airccse.org/journal/ijsc/papers/3312ijsc04.pdf
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