• Gaurav Vyas
• Prof Chetan Gupta
• Dr Kapil Chaturvedi

Customer choose to purchase a given item by looking at these evaluations and surveys. Such substance can be positive or negative audits made by customer who have recently utilized the item. The Machine Learning Calculation can help us to visual portrayal of the information and vectorize the information. This paper presents the Naïve Bayes and Logistic Regression method to investigate the customer behavior. The decision tree classification method achieved improvement in the performance parameters over others. The current issues are examined, and afterward, current answers for these issues are introduced and talked about. The simulation results show that the proposed strategy has higher precision, recall and F1 score. The strategy is end up being effective with high accuracy on remarks. The reproduction and analysis is finished utilizing the python spyder 3.7 software.

Machine Learning, Customer Prediction Model, Decision tree

"Customer Behaviour Analysis in E-commerce Dataset Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 2, page no.d307-d311, February-2022, Available :http://www.jetir.org/papers/JETIR2202341.pdf

"Customer Behaviour Analysis in E-commerce Dataset Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 2, page no. ppd307-d311, February-2022, Available at : http://www.jetir.org/papers/JETIR2202341.pdf