Challenge Aug-2021

Titanic Booking Service                                                                     Solutions

Kaggle is a popular competition website for Machine Learning (ML) professionals. Its legendary Titanic competition is quite simple: use ML to create a model that predicts which passengers survived the Titanic shipwreck. Kaggle offered two CSV files: train.csv – a list of 891 passengers with their various characteristics like age, sex, ticket class, fare, and more; test.csv – a list of other 418 passengers with similar characteristics. Both lists include the field “Survived” that contains 1 if the passenger survived or 0 – if not. The first list should be used as a training set to discover the survival rules, and the second list should be used only to test the accuracy of the discovered survival rules. Note that not all characteristics are known, e.g. for some passengers age is not specified. Many good solutions have been provided since 2012.

In our challenge, we want you to download and use the same two csv-files to create and test a special decision service called “Titanic Booking Service”. First, you should create a decision model with rules that produce one of the following advices for each passenger: 1) Bon Voyage; 2) Go at your own risk; 3) Don’t do it!

You can create rules using any ML tool or manually following your own analysis of the data and your interpretation of the Titanic tragedy (“hints from the future”). You even may borrow some rules discovered by Kaggle‘s competitors. What you cannot do is to feed your ML tool with passengers who should be used for testing only.

At the end your decision model should apply these rules against every of 418 test-passengers, giving them a booking “advice”, comparing them with what actually happened to each passenger, and producing the summary with total numbers of Good and Bad advices.

Use your favorite BR/ML/DM tool to create and run this decision service. Please submit your solutions to We plan to announce winners (people who produce the largest numbers of Good advices) at DecisionCAMP in September.