Analyzing Titanic Disaster using Machine Learning Algorithms

Titanic disaster occurred 100 years ago on April 15, 1912, killing about 1500 passengers and crew members. The fateful incidents still compel the researchers and analysts to understand what could have led to the survival of some passengers and demise of the others. With the use of machine learning methods and a dataset consisting of 891 rows in the train set and 418 rows in the test set, we attempt to determine the correlation between factors such as age, sex, passenger class, fare etc. to the chance of survival of the passengers. These factors may or may not have impacted the survival rates of the passengers. In this research paper, we use various machine learning algorithms namely Logistic Regression, Nave Bayes, Decision Tree, Random Forest to predict the survival of passengers. In particular, we attempt to compare these algorithms.