Detection of Diabetes Using Various Machine Learning Algorithm
Author(s):
Rishav Karanjit
Keywords:
Diabetes, Machine learning, Decision Tree, K-Nearest Neighbour, Random forest, soft voting classifier.
Abstract
Lot of the people around the globe are suffering from diabetics. Diabetes is caused by very high blood glucose. There are different tests available to test diabetes. All of these tests directly or indirectly require assistance from medical personnel. Machine learning can help individuals to detect diabetes without the need of medical personnel. In this paper, we have proposed the solution of detecting diabetes using Decision Tree, K-Nearest Neighbour, Random forest and soft voting classifier which achieved the accuracy of 80.52%, 75.97%, 81.17%, 83.12% respectively
Article Details
Unique Paper ID: 152260

Publication Volume & Issue: Volume 8, Issue 2

Page(s): 700 - 703
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