tirthnisar193 / text-classification

classify text using machine learning algorithms and Deep Learning Algorithms. Created Date: 12 Sept 2018

Created Date: 12 Sept 2018

text-classification-using-machine-learning-algorithms

In machine learning, multiclass or multinomial classification is the problem of classifying instances into one of three or more classes. (Classifying instances into one of two classes is called binary classification.) Multiclass classification should not be confused with multi-label classification, where multiple labels are to be predicted for each instance.

Multi-Classification models

• Random Forest
• Linear Support Vector Machine
• Multinomial Naive Bayes
• Logistic Regression.

In this repo,
1. Data can be found inside the "data" folder
2. bin folder is for the pickle file of each models.
3. MachineLearning Models and DeepLearning Models are inside the "models" folder
4. Small, small modules are inside the "modules" folder.
5. Notebooks are stored in the "notebooks" folder

To test, run main.py

NOTE: Text Classification:

1. Binary Classification: movie reviews, sentiment,ham/spam
2. Multiclass Classification: news
3. Multi Label Classification: news

ML:

1. using TFIDF Vectorizer
2. Using Embeddings