Text_Classification

This model is a usecase of Naive Bayes Algorithm

This is a build using a pipeline where all the training data is vectorized using Tfidfvectorizer which is a preprocessing step and then Naive Bayes algo is applied

The Predictions of model are as below:

Steps to use the model:

1. First Clone the model into your Project Directory :

  open your command promt and write :  git clone https://github.com/mohantyrohan3/Text_Classification-using-Naive-Bayes 

2. Then in your .py app import pickle library and write the following code:

  with open('Text_Classification_model','wb') as f:
              model1=pickle.load(f)

3. Now you are ready to go just start Predicting:

  ans=model.predict(['Absence of Doctors'])
  print(categories[ans[0]])