1,309 passenger records from the 1912 shipwreck categorized by survival status and demographic details. The data includes 12 distinct variables such as passenger class, age, and family relations to support binary classification modeling.
Use Cases
- Build a classification model using 'Sex' and 'Age' to predict the 'Survived' status.
- Apply missing value imputation techniques on the 'Age' and 'Cabin' columns.
- Engineer new features from 'SibSp' and 'Parch' to represent total family size on board.
Strengths
- 1,309 passenger records split into training and test sets for predictive modeling.
- 12 columns including 'Pclass', 'Sex', 'Age', 'SibSp', 'Parch', and 'Fare'.
- Binary target variable 'Survived' indicating the outcome for each passenger in the training set.