Detecting Kidney Disease using Naïve Bayes and Decision Tree in Machine Learning
Sakshi Kapoor1, Rabina Verma2, Surya Narayan Panda3
1Sakshi Kapoor, Chitkara University Institute Of Engineering and Technology Chitkara University, Punjab, India
2Rabina Verma, Chitkara University Institute Of Engineering and Technology Chitkara University, Punjab, India
3Surya Narayan Panda, Chitkara University Institute Of Engineering and Technology Chitkara University, Punjab, India
Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 498-501 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4377119119/2019©BEIESP | DOI: 10.35940/ijitee.A4377.119119
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Chronic Kidney Disease (CKD) mostly influence patients suffered from difficulties due to diabetes or high blood pressure and make them unable to carry out their daily activities. In a survey , it has been revealed that one in 12 persons living in two biggest cities of India diagnosed of CKD features that put them at high risk for unfavourable outcomes. In this article, we have analyzed as well as anticipated chronic kidney disease by discovering the hidden pattern of the relationship using feature selection and Machine Learning classification approach like naive Bayes classifier and decision tree(J48). The dataset on which these approaches are applied is taken from UC Irvine repository. Based on certain feature, the approaches will predict whether a person is diagnosed with a CKD or Not CKD. While performing comparative analysis, it has been observed that J48 decision tree gives high accuracy rate in prediction. J48 classifier proves to be efficient and more effective in detecting kidney diseases.
Keywords: Chronic Kidney Disease (CKD), Classification Techniques- J48, Machine Learning, Naïve Bayes.
Scope of the Article: Machine Learning