alina-cai / titanic-survival

Titanic Survival Prediction

This project uses a RandomForest classifier to predict survival on the Titanic. It is based on a binary classification problem where the goal was to predict whether a passenger survived the Titanic disaster or not, based on various personal attributes and information.

The final accuracy obtained was 81.46%.

Main Steps Involved

The dataset was acquired from Kaggle.

Data Cleaning & Preprocessing: Handling missing values, dropping irrelevant columns, and feature engineering.

Data Visualization: Used matplotlib and seaborn for visualizing data distributions and relations between different features.

Model Development & Evaluation: Built a Random Forest Classifier and evaluated the model using a validation set.