This is a Women’s Clothing E-Commerce data-set revolving around the reviews written by customers
We have considered 'Rating' as the Target variable. The main objective is to predict the Women's clothing rating based on the customer reviews.
This dataset includes 23486 rows and 10 feature variables. Each row corresponds to a customer review, and includes the variables:
Clothing ID: Integer Categorical variable that refers to the specific piece being reviewed.
Age: Positive Integer variable of the reviewers age.
Title: String variable for the title of the review.
Review Text: String variable for the review body.
Rating: Positive Ordinal Integer variable for the product score granted by the customer from 1 Worst, to 5 Best.
Recommended IND: Binary variable stating where the customer recommends the product where 1 is recommended, 0 is not recommended.
Positive Feedback Count: Positive Integer documenting the number of other customers who found this review positive.
Division Name: Categorical name of the product high level division.
Department Name: Categorical name of the product department name.
Class Name: Categorical name of the product class name.