Machine learning algorithms on Titanic Data (Kaggle Challenge)

Approach

Differents Algorithms to best predict is a passenger on titanic would have died or lived Models implemented

Simple Models

• Naive Bayes
• K Nearest Neighbors
• Decision Tree
• Support vector Machine

Ensemble Models

• Random forest
• Adaboost
• Gradient Boosting
• Stacking (manual and automatic stacking, voting)

Contributing

Papermark is an open-source project and we welcome contributions from the community. If you'd like to contribute, please fork the repository and make changes as you'd like. Pull requests are warmly welcome.

Kaggle : https://www.kaggle.com/competitions/titanic