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An improved random forest algorithm for classification in an imbalanced dataset

Publication Type : Conference Paper

Publisher : URSI Asia-Pacific Radio Science Conference, AP-RASC 2019

Source : URSI Asia-Pacific Radio Science Conference (AP-RASC)

Campus : Amritapuri

School : School of Computing, School of Engineering

Center : Computer Vision and Robotics, Research & Projects

Department : Computer Science

Verified : Yes

Year : 2019

Abstract : 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. © 2019 URSI. All rights reserved.

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