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Customer Behaviour Prediction

Kulkarni, Nikhil (2020) Customer Behaviour Prediction. Masters thesis, Dublin, National College of Ireland.

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In this paper customer behaviour prediction models are applied on data which is realworld e-commerce data over a period of 4.5 months, The main aim of the research is to predict customer buying habits and recommend items according to behavioural data of customers. For predictive research, insight into consumer actions may be obtained to improve business decision-making. Comparing the statistical approach to data mining in predicting customer behaviour, In this study Comparison analysis is performed in between Logistic regression, LightFM and Multilayer perceptron with label encoding and hyperparameter optimization. As a result, MLP achieved 92.4 % accuracy, An accuracy of LightFm is 81.6% and For Logistic 79.40. Altogether MLP displayed better results but execution time could have been reduced.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Dan English
Date Deposited: 22 Jan 2021 14:49
Last Modified: 22 Jan 2021 14:49

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