In this report I will provide an overview of my solution to kaggle’s “Titanic” competition. The aim of this competition is to predict the survival of passengers aboard the titanic using information such as a passenger’s gender, age or socio-economic status. I will explain my data munging process, explore the available predictor variables, and compare a number of different classification algorithms in terms of their prediction performance. All analysis presented here was performed in R. The corresponding source code is available on github.

Data munging

The data set provided by kaggle contains 1309 records of passengers aboard the …