This project uses machine learning to create a model that predicts which passengers survived the shipwreck of the Titanic.
In this competition, you’ll gain access to two similar datasets that include passenger information like name, age, gender, socio-economic class, etc. One dataset is titled train.csv and the other is titled test.csv. Train.csv will contain the details of a subset of the passengers on board (891 to be exact) and importantly, will reveal whether they survived or not, also known as the “ground truth”. The test.csv dataset contains similar information but does not disclose the “ground truth” for each passenger. It’s your job to predict these outcomes. Using the patterns you find in the train.csv data, predict whether the other 418 passengers on board (found in test.csv) survived.
prediction-titanic.ipynb: This work has a result of 0.73923 titanic.ipynb: This work has a result of 0.72727
In the latest version of the project, two methods of data prediction were used (RandomForestClassifier and GradientBoostingClassifier) All code is commented, the best result was shown by GradientBoostingClassifier Score: 0.77511
The code will be improved in the future.