Framework for Choosing a Supervised Machine Learning Method for Classification Based on Object Categories : Classifying Subjectivity of Online Comments by Product Categories
Alexandre St-Vincent Villeneuve, Michel Plaisent · 2023
The core objective of this research is to develop a methodology for selecting a supervised machine learning classification technique based on the specific categories of objects that need to be classified. The study focuses on product categories extracted from Amazon's Product Reviews database, which are utilized to evaluate the subjectivity of post-purchase feedback. The primary supervised machine learning methods are utilized to efficiently perform the classification task. The resulting insights will enable the prioritization and choice of the best approach based on the selected categories. In the context of accelerated technological adoption due to the COVID-19 pandemic, this research contributes by showcasing how AI/ML can play a pivotal role in enhancing decision-making processes across various sectors and highlighting the significance of adapting to emerging technologies for sustainable growth.