In this project, I analyzed the Titanic dataset and prediced the surival rates of the passengers on-board.
- drop values that won't be useful to analysis
- add a variable in Sex where 0 is female, 1 is male
- P class variables
- Create random ages based on avg, std, and null freq
- Fill null spots in Age
- fill null values in Embarked
- fill null spot in Fare
- features used to train: Pclass, Fare, male or not, and Age
- label used to train: Survived
- Used MLPClassifier
1.00 is the best possible ROC AUC, higher is better.