• Pamulapati Sri Madhu Chowdary
• Anbarasi M

Rainfall is the most crucial process of nature. All the living beings rely on water and rainfall is a process that is responsible for the continual process of the water cycle. Many human activities like agriculture are dependent on rainfall, especially in a country like India. Thus, it is essential and necessary to predict the rainfall patterns to estimate the flooding and drowning events. Application of data mining algorithms is the best way to forecast rainfall. This paper outlines the use of stacking technique to predict rainfall. In stacking technique, there are two layers - the first layer is considered as the meta layer and the second layer is considered as the base layer. Classification techniques such as Bayesian, decision tree, support vector machine, and K nearest neighbor are used in the base layer and in the meta layer, dip neural networks provide greater accuracy for ensemble techniques.

Stacking; Data Mining; Ensemble; Rainfall; Deep Neural Network.

"Enhanced Rainfall Predictions using Stacking Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 7, page no.750-755, July-2020, Available :http://www.jetir.org/papers/JETIR2007394.pdf

"Enhanced Rainfall Predictions using Stacking Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 7, page no. pp750-755, July-2020, Available at : http://www.jetir.org/papers/JETIR2007394.pdf