Titanic - Model for a Disaster!

    The Titanic classification problem is widely known for beginners, so I used my basic knowledge to answer the question "Will you survive?".

Tech Stack

• Python: Version 3.10

• Scikit-Learn: Version 1.1.2

• Pandas: Version 1.4.3

Details

• Feature engineering was the best thing I learned in this project; I dropped the nan columns because they were misleading for the classification algorithm. Then I replaced the nan values with the coulmn's mean.

• I splitted the dataset to 70% Train and 30% Test.

• I tried eight different classification algorithms and the results was as following:

LogisticRegression score is : 84.7

DecisionTreeClassifier Score is : 80.6%

KNeighborsClassifier Score is : 74.63%

GaussianNB Score is : 79.1%

SVC Score is : 67.54%

Perceptron Score is : 76.49%

SGDClassifier Score is : 81.34%

RandomForestClassifier Score is : 78.73%

Contributing

Contributions are what makes the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Do not forget to give the project a star! Thanks again!

License

Distributed under the MIT License. See LICENSE.txt for more information.

References

• The Kaggle competition

Contacts

• Via Email : [email protected]
• Via LinkidIn : https://www.linkedin.com/in/abonady/