alicevillar/titanic-kaggle
Titanic rescue prediction using Decision Tree, SVM, Logistic Regression, Random Forest and KNN. The best accuracy score was from Random Forest: 84.35%
This project helps data science enthusiasts and beginners learn how to build a classification model. You input historical passenger data, including details like gender, age, and passenger class, and the project outputs predictions on who would survive or perish. It's designed for someone learning fundamental machine learning concepts through a classic dataset.
No commits in the last 6 months.
Use this if you are a beginner in data science looking for a documented example of building and comparing different machine learning models for a classification problem.
Not ideal if you need a production-ready model for real-time predictions or an advanced, novel approach to classification.
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Last pushed
Jun 09, 2021
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