Implementation of Fraudulent Sellers Detection System of Online Marketplaces using Machine Learning Techniques

The E-commerce proportion in global retail expenditure has been steadily increasing over the years showing an obvious shift from brick and mortar to retail clicks. To analyze the exact problem of building an interactive models for the identification of auction fraud in the entry of data into ecommerce. This is why the most popular site's business develops with retailers and other auction customers. Where viral customers purchase products from online trading, customers may worry about fraudulent actions to get unlawful benefits from honest parties. Proactive modesty systems for detecting fraud are thus a necessary practice to prevent such illegal activities. The shopping product is built according to the customer's requirements and is safer online and resting, and the rules and regulations that are necessary to follow no longer seem to be the best of workable selection, coefficient limits that facilitate the shopping product and make it easier for the user model to compete on each platform so that it can experiment.