Using decision tree classifier to predict income levels

Sisay Menji Bekena

MPRA Paper from University Library of Munich, Germany

Abstract: In this study Random Forest Classifier machine learning algorithm is applied to predict income levels of individuals based on attributes including education, marital status, gender, occupation, country and others. Income levels are defined as a binary variable 0 for income

Keywords: random-forest classifier; data science (search for similar items in EconPapers)
JEL-codes: A10 D1 D10 (search for similar items in EconPapers)
Date: 2017-07-30
New Economics Papers: this item is included in nep-big and nep-cmp
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:83406

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