一种用于不平衡数据集分类的改进随机森林算法。

2019 URSI Asia-Pacific Radio Science Conference (AP-RASC) Pub Date : 2019-03-01 DOI:10.23919/URSIAP-RASC.2019.8738232

C. Jose, G. Gopakumar

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引用次数: 7

摘要

如今，机器学习算法在工业应用中得到了广泛的应用。这些算法经过多次修改和微调，以改进现有产品并获得更好的结果。在本文中，我们分析了“IDA 2016挑战”中提出的一个工业问题，并在确定为挑战一部分的最佳解决方案的基础上提出了改进的解决方案。

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An Improved Random Forest Algorithm for classification in an imbalanced dataset.

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.

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2019 URSI Asia-Pacific Radio Science Conference (AP-RASC)

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