E-Commerce Product Classification Using Supervised Learning Models


  • Norsyela Muhammad Noor Mathivanan
  • Nor Azura Md. Ghani
  • Roziah Mohd Janor
  • . .






Text Classification, E-commerce product, Supervised Learning Model


E-commerce has become a major player in today’s marketplace having a large database of products and number of retailers and consumers use these services. However, these products are placed into different categories according to the structure of different websites. An automatic classification model helps in classifying the products efficiently. This paper presents a comparative study on different algorithms from supervised learning model to classify real-world datasets related to e-commerce products. The results show that KNN is the best model with the highest accuracy to classify the data used in the study. Hence, KNN model is a good approach in classifying e-commerce products.




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