SayamAlt / E-Commerce-Text-Classification

Successfully established a machine learning model that can accurately classify an e-commerce product into one of four categories, namely "Books", "Clothing & Accessories", "Household" and "Electronics", based on the product's description.

About Dataset

This is the classification based E-commerce text dataset for 4 categories - "Electronics", "Household", "Books" and "Clothing & Accessories", which almost cover 80% of any E-commerce website.

The dataset is in ".csv" format with two columns: the first is the class name, and the second is the datapoint of that class. The data point is the product and description from the e-commerce website.

The dataset has the following features :

Data Set Characteristics: Multivariate

Number of Instances: 50425

Number of classes: 4

Area: Computer science

Attribute Characteristics: Real

Number of Attributes: 1

Associated Tasks: Classification

Missing Values? No

Gautam. (2019). E commerce text dataset (version - 2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3355823