TrixiaBelleza / Automated-Text-Classification

An automated text classification using machine learning approaches such as a Multi-label One-vs-Rest scheme and a Support Vector Machine

Automated-Text-Classification

An automated text classification using machine learning approaches such as a Multi-label One-vs-Rest scheme and a Support Vector Machine

The FetchData directory contains: algo_cmp_kfold.py (For graphs, statistics, and algorithm comparisons) createTable.py (Code in creating table in MySQL) insert2_data.py (Code for inserting data to MySQL) load_model.py (Code for predicting, this was used as test code only. This was not used in the actual app.) train_data.py (Code for training the data and producing models)

The extension-app directory contains: contentScript.js (Main APP) server.py (MAIN LOCAL SERVER) server2.py (Used as testing server, not used in the actual app.)

To Start Training:

1. Store items to database *** createTable.py *** insert2_data.py
2. Run train_data.py