Heart Disease Prediction Using Associative Relational Classification Technique (Acar) With Som Neural Network
Journal Title: International Journal of Modern Engineering Research (IJMER) - Year 2014, Vol 4, Issue 2
Abstract
Mining of medical diagnoses of data is very difficult task in current data mining approach. The heart disease data is collective information of blood pressure, Cholesterol problem, diabetes and another complex disease. The relational of one disease to another is rare so classification task is very difficult. So prediction of heart disease is very critical. in the process of data mining rule based classification technique used for prediction. The rule based classification technique based on association rule mining. The better rule mining technique the better classification and predication of heart disease. in this paper proposed a association based ensemble classification method for heart disease prediction. the association ensemble classifier based on association rule mining and self –organized map network model. For the association rule used Apriori-like algorithm. This algorithm generates numbers of rules for all combination of factor of heart disease and divided into different level such as high level , middle level and low level, the all level ensemble through SOM network and generate optimized set of heart disease prediction.
Authors and Affiliations
Amit Sahu
Keywords
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