Authors :
Vivek Joshi; Shipra Goswami; Shalini Goel
Volume/Issue :
Volume 7 - 2022, Issue 4 - April
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3MEk331
DOI :
https://doi.org/10.5281/zenodo.6569964
Abstract :
With the promises of predictive analysis in
machine learning algorithms, prediction of future is no
longer a difficult task. Many efforts have already been
done to obtain useful knowledge from it. In this paper, we
will apply five machine learning algorithms on three
different set of medical data. The objective of this
research paper is to predict heart disease, diabetes and
liver disease by using different machine learning
algorithms that are Naïve Bayes Algorithm, Support
Vector Machine, Decision Tree, KNN, Logistic Regression
and find the most efficient one.
Keywords :
Machine Learning, Naïve Bayes Algorithm, SVM, KNN, Regression, Decision Tree and Logistic Regression.
With the promises of predictive analysis in
machine learning algorithms, prediction of future is no
longer a difficult task. Many efforts have already been
done to obtain useful knowledge from it. In this paper, we
will apply five machine learning algorithms on three
different set of medical data. The objective of this
research paper is to predict heart disease, diabetes and
liver disease by using different machine learning
algorithms that are Naïve Bayes Algorithm, Support
Vector Machine, Decision Tree, KNN, Logistic Regression
and find the most efficient one.
Keywords :
Machine Learning, Naïve Bayes Algorithm, SVM, KNN, Regression, Decision Tree and Logistic Regression.