• P. Rajasree
• B. Vimala devi
• S. Gomathi

The main objective of the paper is to implement classification and clustering algorithm such as Naive Bayes, K-Means, and Farthest First clustering algorithm using Weka to analyse airline dataset. In addition to that, performance analysis of these algorithms shows that Farthest First outperforms the other algorithms. Data set has been obtained from UCI machine learning repository. The algorithms has been discussed with the results obtained from the tool. The confusion matrix for classification algorithm and the cluster instances for clustering algorithm is also shown in the result.

"IMPLEMENTATION OF MACHINE LEARNING IN AIR LINE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.220-223, June 2019, Available :http://www.jetir.org/papers/JETIRDC06039.pdf

"IMPLEMENTATION OF MACHINE LEARNING IN AIR LINE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp220-223, June 2019, Available at : http://www.jetir.org/papers/JETIRDC06039.pdf