In this assignment, you will complete the implementation a decision tree. All the resources you need are provided in a single zip file: pa4-resources.zip.
The resources comprise three directories: the Java source files for a code framework, the Javadoc for the code framework, and some data for your experiments. You should first read all the Javadoc, concentrating especially on AttributeSet, InstanceSet, and Distribution. (Click on index.html to start reading.) Don't bother reading all of the source files; consult these as needed, if and when the Javadoc proves to be insufficient.
Glance at the data files (each has the extension .arff) using a text editor. A constructor for InstanceSet automatically reads a .arff file, so you need not interact with these files directly, but it will help to have some familiarity with these files when debugging your code. The file format is fairly obvious and is not described further here.
The three data files provided are weather.nominal.arff, contact-lenses.arff, and soybeanB.arff. The first file is a fake data set for deciding whether or not to play tennis based on the current weather conditions, authored by Witten and Frank and provided with their Weka machine learning software. This is a small, almost trivial machine learning problem; it's not very interesting, but an extremely useful file for debugging. The second file is a real data set for determining what type of contact lenses to prescribe to a patient based on their condition. The third file is a real data set for determining what type of disease a soybean has (although the file has been edited to remove so-called missing data, which we don't deal with in this assignment). Both the second and third files are part of a well-known collection of machine learning data collated and distributed by the University of California, Irvine, and known as the UC Irvine Machine Learning Repository.
To complete the assignment, add and/or alter code at the nine locations of the string "TODO" in the three source files DecisionTree.java, DecisionTreeInternal.java, and DecisionTreeLeaf.java. When finished, your code should successfully and correctly generate decision trees for all three provided data files. This is accomplished in the main method of DecisionTree, which accepts a single commandline argument: the name of the .arff file to be used. Do not edit or add code at any location other than the "TODO" markers.
To turn in this assignment, submit a single ZIP file containing the three source files DecisionTree.java, DecisionTreeInternal.java, DecisionTreeLeaf.java to Moodle. Grading will be based on the standard criteria for grading code in this course, as listed on the main assignments page.