At this point, we have a decent set of variables that can help predict whether a passenger survived the Titanic disaster. However, that data could use a bit of cleaning up in order to handle outliers and missing values. We could also try to extract other meaningful features from existing attributes to boost our predictions. In other terms, we want to do some feature engineering. Feature engineering is the key to boosting the accuracy of your predictions.
Feature engineering is the process of using domain knowledge of the data to create features that make machine learning algorithms work. ...
