An Efficient Classifier using Multilayer Perceptron for Classification of Liver patient

Abstract

In medical science, Liver patients have been continuously increasing due to excessive consumption of alcohol, inhale of harmful gases, intake of contaminated food and drugs. Classification is one of the important techniques for classification of any type of data. This research work focus on the development of efficient model for classification of liver patient disease. These classifiers are very helpful for doctors to identify such types of diseases. In this research work, we will use MLP to develop the robust classifier which can classify data as lover or non liver. We have applied ILPD data set on MLP with different learning and different hidden layers. Our proposed model MLP achieved 77.77% of accuracy in case of hidden layer 2 and learning rate 0.7 as robust model.

Authors and Affiliations

Pooja Shrivastava, Yukti Kesharwani

Keywords

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  • EP ID EP22333
  • DOI -
  • Views 208
  • Downloads 4

How To Cite

Pooja Shrivastava, Yukti Kesharwani (2016). An Efficient Classifier using Multilayer Perceptron for Classification of Liver patient. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(6), -. https://europub.co.uk./articles/-A-22333