Machine Learning

Naïve Bayes Classifier for Titanic Dataset

Uses a Multinomial Naïve Bayes model to predict passengers’ embarkation port from key demographic and fare features.

Jun 2024 Eng. Ameen Qahtan

Project Overview

The project loads the Titanic CSV, fills missing values (Age, Fare, Embarked) using medians to avoid warnings, and label-encodes categorical data. It selects features (Pclass, Sex, Age, SibSp, Parch, Fare) with the target set to “Embarked.” After splitting into train/test sets, it trains a MultinomialNB classifier and evaluates performance via accuracy, confusion matrix, and classification report .