Passenger data analysis of Titanic using machine learning approach in the context of chances of surviving the disaster

Titanic disaster occurred about 100 years back but still it attracts the researchers to understand and study that how some passengers survived and others perished. In this work, the characteristics of the passengers will be identified and the relationship of survival chance from the disaster is found. Feature engineering techniques will be performed, where the alphabetic values will be changed to numeric values, the family size will be calculated. Also, we will extract the title from the name, and deck label from ticket number. Classification is done using Decision tree machine learning classification algorithm using two classes which are survived and not survived. R programming has been used for its implementation. Clustering is performed using KMeans machine learning algorithm. Its implementation has been done using Python programming.