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Predicting Titanic passenger survival

This project was completed in week 2 of the Data Science Bootcamp at Spiced Academy.

The goal is to predict what passengers would survive the Titanic sink, based on information like gender, cabin, family, and ticket price. This is an ongoing Kaggle competition, where you can find the datasets used for the analyis and my submission.

Classification models

  • Logistic Regression: 82% accuracy (on the kaggle competition: 74.641%)
  • Decision Tree: 78% accuracy
  • Random Forest Classifier: 80% accuracy
  • Ensemble Model: 93% accuracy

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Classification models for passenger survival

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