Code trials for the Titanic ML challenge on Kaggle
Used the random forest classifier so far, with about 74-85% accuracy. Reviewing alternate methods of manually analyzing data.
References -
- Competition page: https://www.kaggle.com/c/titanic/
- Pandas documentation: https://pandas.pydata.org/pandas-docs/stable/pandas.pdf
- Binning: https://pbpython.com/pandas-qcut-cut.html
- Adding columns: https://www.geeksforgeeks.org/adding-new-column-to-existing-dataframe-in-pandas
- sklearn's RandomForestClassifier: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html
- Solution reference: https://www.kaggle.com/startupsci/titanic-data-science-solutions
- Alexis B. Cook's Titanic tutorial: https://www.kaggle.com/alexisbcook/titanic-tutorial