Product Review Classification using Machine Learning and Statistical Data Analysis
Kajal Singh
Kajal Singh, Dartmouth College Hanover, NH, USA.
Manuscript received on 08 March 2023 | Revised Manuscript received on 21 June 2023 | Manuscript Accepted on 15 July 2023 | Manuscript published on 30 July 2023 | PP: 91-96 | Volume-12 Issue-2, July 2023 | Retrieval Number: 100.1/ijrte.A75300512123 | DOI: 10.35940/ijrte.A7530.0712223
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The aim of the paper is to implement and analyze the machine learning models for product review dataset. The project focuses on binary classification, multi-class classification, and clustering approaches to analyze and categorize product reviews. The performance of the models over each of the five classification tasks is measured by the 5-fold cross-validation scores over the training data.
Keywords: Machine Learning, Classification, Clustering, Product
Scope of the Article: Clustering