DISCRIMINATION OF HEART RATE VARIABILITY USING DECISION TREES AND MLP NETWORKS
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 2
Abstract
The main objective of the paper is to analyze the heart rate variability (HRV) of various subjects. The ECG signals collected from the public data base is Categorized using the Classification and Regression Tree (CART). The techniques analyzed in this paper is to minimize the fault occurrence during the decision tree construction and optimize the tree size using the Multi layer Perceptrons(MLP) with the help of online node fault injection training algorithm. To find the proof of convergence the probability of the error in the perceptrons is calculated using mean square error method from this efficiency of the algorithm can be identified.
Authors and Affiliations
Gomathi. S , MohanRaj. T , SaranyaSri. R
Keywords
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