This is a practice on the competition on Kaggle, and I refer to the material from this repo
This competition provides three csv files(train.csv, test.csv, gender_submission.csv(sample))
The Titanic passengers data (train.csv & test.csv) tell us:
Attribute | Definition |
---|---|
Age | Age in years |
Cabin | Cabin number |
Embarked | Port of Embarkation(C = Cherbourg, Q = Queenstown, S = Southampton) |
Fare | Passenger fare |
Name | |
Parch | # of parents / children aboard the Titanic |
PassengerId | |
Pclass | Ticket class(1 = 1st, 2 = 2nd, 3 = 3rd) |
Sex | Gender |
SibSp | # of siblings / spouses aboard the Titanic |
Survived | Survival(0 = No, 1 = Yes) |
Ticket | Ticket number |
We need to give a prediction data (submission.csv) that includes:
PassengerID | Survived |
---|---|
# | 0 or 1 |
Features: Feature engineering, Supervised Learning.
Reference: [資料分析&機器學習] 第4.1講 鐵達尼號災難生存預測