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      • Faculty Publications  (2)

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      • 2020
      • Working Paper

      Machine Learning for Pattern Discovery in Management Research

      By: Prithwiraj Choudhury
      Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
      Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis
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      Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
      • August 2018 (Revised April 2019)
      • Supplement

      Chateau Winery (B): Supervised Learning

      By: Srikant M. Datar and Caitlin N. Bowler
      This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details
      Keywords: Data Science; Clustering; Analytics and Data Science; Customers; Marketing; Analysis
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      Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
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