Blog-Classifier

Introduction

• This is small tool to classify blog in categories using random-forest.
• Training set is in blogs.csv in following format
• To predict category for blog you've to use use_forest_prediction.py. May be you can change the way data is provided to the function to integrate with backend.

   |----------------------|
   |   blog  |  category  |
   |----------------------|

Installation

• Installing dependency from requirements.txt using following command

   pip install -r requirements.txt

• Training from blogs.csv (save model in forest.pickle and vocab.pickle)
• run following command in folder.

   python bag-of-words.py

• comment out 15th line in bag-of-words.py after downloading stopwords from popup.

Make Prediction

• In order to make prediction,Run `user_forest_prediction.py'

   python user_forest_predition.py

• Basically,Collection blog is collected from following urls with scrapy framework.So Random blog will not provide good results.

  • tsa - https://www.dhs.gov/archive/news-releases/blog
  • air-traffic - http://www.atc-network.com/atc-news

• Reference: https://www.kaggle.com/c/word2vec-nlp-tutorial/details/part-1-for-beginners-bag-of-words