CLASSIFICATION OF GENDER BASED FOCUS MAPPING FOR EPILEPSY PATIENTS USING ROUGH SETS

Abstract

The objective of this work is to classify the mind mapping decisions “like”, “dislike” and “neutral” in Epilepsy patients by applying the concepts of rough sets. An effective rough set-based classification of mental status in epilepsy patients has been computed using the features such as meditation, familiarity, theta, attention, appreciation, beta, mental effort, delta, alpha and gamma. The significance of features is considered as conditional attributes and the expected mood is represented as decision attributes. To analyze the impact of the features, the cardinality and rough set-based approximation are computed. Grey Relational Analysis (GRA) algorithm is applied for classification of patient decision is either like or dislike or neutral. The experimental results on classification of mind mapping of epilepsy patients using rough set-based approximation yields 95% accuracy.