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Understanding Random Forests: From Theory to Practice
[article]
2015
arXiv
pre-print
Data analysis and machine learning have become an integrative part of the modern scientific methodology, offering automated procedures for the prediction of a phenomenon based on past observations, unraveling underlying patterns in data and providing insights about the problem. Yet, caution should avoid using machine learning as a black-box tool, but rather consider it as a methodology, with a rational thought process that is entirely dependent on the problem under study. In particular, the use
arXiv:1407.7502v3
fatcat:vb62j3zs7ndwnbmiula3exwqea