ISSN : 2319-7323

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE ENGINEERING

ABSTRACT

Title	:	Design and Analysis of Data Mining Based Prediction Model forParkinson�s disease
Authors	:	Chandrashekhar Azad, Sanjay Jain, Vijay Kumar Jha
Keywords	:	Parkinsons, Data mining, Decision tree, ID3, Decision Stumps.
Issue Date	:	May 2014
Abstract	:	Purpose: The purpose of this research paper is to develop a prediction model for Parkinson�s disease. There are many symptoms that lead to Parkinson�s disease such age- environmentalfactor, trembling in the legs, arms, hands, impaired speech articulation and production difficulties. In this research paper speech articulation of Parkinson�s disease affected people is considered for model formation and analyzes the model based on the symptom of disease. Methods: In proposed prediction model tree based classification model decision tree, ID3 and decision stumps are used for training and testing the effectiveness of proposed prediction model. Here we also applied K �fold cross validation technique for true prediction so that each record is sued for training and testing. Results : In proposed model decision tree based our prediction model provide accuracy 85.08%, classification error 14.92%, ID3 provide accuracy 75.33% ,classification error 24.67% and decision stumps based model proved accuracy 83.55% and classification error 16.45%. Conclusion:Proposed model based on Decision tree provide best result in comparison to other in terms of parameters accuracy and classification error.
Page(s)	:	181-189
ISSN	:	2319-7323
Source	:	Vol. 3, No.3