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Predicting revenue generation in an online retail website using machine learning algorithm

Srinivasan, Annadurai (2020) Predicting revenue generation in an online retail website using machine learning algorithm. Masters thesis, Dublin, National College of Ireland.

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Abstract

E-commerce has been the hot spot for business in today's world.Every day millions of people spend their time buying, selling and surfing on the internet. The main motive of any business is to generate optimal revenue. The most vital aspect in e-commerce is to track any potential buyer and try to generate income. The previous studies conducted were focused more on the deep learning. The biggest drawback in using deep learning models is that, it consumes a lot of time to run the model, which is not optimal in the real-world scenario. In this research, both the techniques of undersampling and oversampling were implemented. ANOVA was used for feature selection which aided in reducing the noise in the dataset by removing unwanted features, which in return increased the performance of machine learning models. A significant increase in accuracy was observe by combining XG Boost classifier with oversampling technique.

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

H Social Sciences > HF Commerce > Electronic Commerce
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Dan English
Date Deposited: 18 Jun 2020 15:31
Last Modified: 18 Jun 2020 15:31
URI: http://trap.ncirl.ie/id/eprint/4310

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