An Improved Random Forest Algorithm for classification in an imbalanced dataset
Christy James Jose, G. Gopakumar · 2019
Nowadays machine learning algorithms are being used extensively in industrial applications. Many a times these algorithms are modified and fine tuned so as to improve the current products and get better results. In this paper, we analyse an industrial problem that was put forward in the ‘IDA 2016 challenge’ and propose an improved solution over the best solution identified as part of the challenge.