In which we take our final stab at the titanic challenge by ‘throwing the kitchen sink’ at the problem, setting up another 5 different machine learning models and seeing if they improve our performance (hint they do not, but hopefully it's still interesting) Source: https://somewan.design An Actuary learns Machine Learning – Part 4 – Error correction/data cleansing/Feature Engineering10/1/2021 
In which we do more data exploration, find and then fix a mistake in our previous model, spend some time on feature engineering, and manage to set a new high-score. Source: https://somewan.design |
AuthorI work as a pricing actuary at a reinsurer in London. Categories
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