Created Date: 12 Sept 2018
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:
- Binary Classification: movie reviews, sentiment,ham/spam
- Multiclass Classification: news
- Multi Label Classification: news
ML:
- using TFIDF Vectorizer
- Using Embeddings