Surviving the Titanic tragedy: A sociological study using machine learning models

Sociological transactions play an important role in human behaviour and social standing. The Titanic was the perfect example as the passengers belonged to high income, middle-income, and low-income groups. It is interesting to see how social factors influenced who was going to survive. The data was collected from the website “Kaggle.com”, and machine learning algorithms were applied after carrying out an exploratory and visual analysis. The hypothesis that women and children were saved (which became famous after Steven Spielberg’s Titanic (1975)) was tested by random forest algorithm as well as the hypothesis that family density played a major role in survival. The results showed that title and sex were the most important factors influencing if the passenger was to survive.