A Comparative Study of Hybrid Evolutionary Based Algorithms with Machine Learning Classifiers for the Prediction of Medical Database

In the current world, day-by-day, huge amount of data being generated at a rate far higher than by which it can be examined by human comprehension alone, in this case, data mining became an important task for extracting useful information from large amount of data. Especially in these cases, the standard techniques of datamining plays in a better way such as Evolutionary approaches performs more efficient as well as more accurate. The objective of this paper is to compare Fuzzy based Evolutionary Algorithm with other machine learning classifiers to improve the classification of medical dataset of heart disease.