A machine learning solution to a marketing problem

This essay presents a marketing problematic along with a way of solving it with the help of statistical tools. Precisely, a Recommender System is built to address a marketing problem for a supermarket in Germany. Both the the- oretical and the practical aspects of the use of Machine Learning methods are underlined. Our focus is oriented in two parts. First, we define precisely a problem, from the conceptual meaning to its natural mathematical transla- tion. Second, we provide an analysis that is anchored to business constraints, on top of being an academic paper. Highlight is made on unifying notations for this specific problem, and on comparing different methods before and after their implementation. This work is designed to fulfill the Master’s thesis re- quirements with advanced statistical approach. Mathematical background is emphasized in parallel with hands-on implementation using the open source software R.

Grantor dc:publisher

Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät

Year dc:date.issued

2014

Author dc:creator

• Revert, Félix

• Machine Learning
• Recommender System
• Naive Bayes
• k Nearest Neighbors

Statement dc:rights

• Namensnennung

Licence dc:rights.uri

• http://creativecommons.org/licenses/by/3.0/de/

Language dc:language.iso

eng

DOI

https://doi.org/10.18452/14222

OAI record oai:identifier

https://edoc.hu-berlin.de/server/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Aedoc.hu-berlin.de%3A18452%2F14874