Categoriation the ecommerce products to their category tree and brand using machine learning.
This repository contains data, model training and testing code, input file
content of the repository:
1)"data" Folder contains a csv format dataset i.e"dataset.csv", and a folder named as sub_category that contains the data for each subcategory that comes under main category. The files with data have 4 columns that are (name,brand,category1,category2).
2)"input.txt" contains the input for the test that is entered maually for the model.
3)"main.py" this python code first build a model then with cross_validation data finds accuracy and then takes names from input file and predict their category tree and brand.