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Overview:

This project aims to predict whether passengers on the Titanic survived based on their personal information, such as age, gender, and class. The model is developed using the Decision Tree algorithm, which is trained on historical passenger data to make survival predictions. Model performance is evaluated using the AUC (Area Under the Curve) metric.

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Key Features:

1. Decision Tree Model:

The model is built using the Decision Tree algorithm, which is highly interpretable and effective for classification tasks like predicting survival outcomes based on passenger information.

2. Training with Passenger Data:

The model is trained on real Titanic passenger data, including variables like age, gender, ticket class, and more, to learn patterns associated with survival.

3. AUC Validation:

The model’s performance is validated using the AUC (Area Under the Curve) score, a reliable metric to evaluate classification models by measuring their ability to distinguish between survival outcomes.

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Links:

• GitHub