Classification: Predicting Passengers Survivability of Titanic
This is the Data Science Competition Project “Titanic: Machine Learning from Disaster” from Kaggle. The goal of this project was to predict the survivability of Titanic Passengers.
The dataset consists of informations about the passengers such as the name, gender, age, fare, cabin number and so on. The project involves cleaning of the data, feature selection, exploratory data analysis and making a prediction model.
The prediction model was build based on some selected features from exploring the dataset using a Random Forest model. The model achieved an accuracy of 80.8% and placed me in the top 7% of all participants.
Here is an example of the result from the analysis of gender in the project:
Women are always highly prioritized to be saved first. That explains the high number of female survivors compared to males.
Another example (exploring the title name of passengers):
See the full project here: