Connect-4 is popular two-player game similar to tic-tac-toe. Connect-4 is a solved game and one can compute the winner for every position of the game.
The Connect-4 data set from the UCI Machine Learning Repository contains all legal positions in the game of connect-4 in which neither player has won yet, and in which the next move is not forced. The outcome class is the theoretical value of the game from the perspective of the first player. Full details about the format of the training data is available via the Data Set Description link on the UCI page.
In this assignment you have to build three classifiers for this data set: a decision tree, a naive Bayesian classifier, and a support vector machine. Do 10-fold cross validation to evaluate your classifier.
You can use any programming language, including Python and R. You can make use of standard packages for analytics and machine learning. Clearly document any external packages used by your code.
Submit via Moodle a single archive (zip, tar.gz, …) containing:
The code you used to solve the assignment.
A link to the output produced by your code. Do not include the output in this submission. Save it somewhere on the cloud and provide a link.
A short write up describing how your code ran on the data sets: the parameters used, time taken, space required, and anything else of interest.
You can work in groups of two. Each group makes a single submission to Moodle. Use either person's Moodle account to submit. The submission should mention the names of the two partners.
There will be a short oral presentation and question/answer session for each group.