• R. Mahesh,
• R. Priyanga,
• S. Gomathi

The main objective of the paper is to find the best machine learning algorithm to predict the population outcome in the future. This paper discusses about the three algorithms, which are naïve Bayes, IBk and Random Trees. Machine learning tool used for running these algorithms is WEKA. In this test, WEKA is used to analyze the data and the three algorithms are added from the library. The data set is obtained from UCI repository and from number of instances available in the dataset, only limited number of instances is used to run the algorithm to keep the controlled environment for this test. Of all the three algorithms Naïve bayes algorithm shows the highest result.

Machine learning, Naïve Bayes, Weka, Lazy IBk, Random trees, UCI repository

"Population Prediction Using Machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.189-192, June 2019, Available :http://www.jetir.org/papers/JETIRDC06033.pdf

"Population Prediction Using Machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp189-192, June 2019, Available at : http://www.jetir.org/papers/JETIRDC06033.pdf