Automated Learning and Adaptive Knowledge Systems Homework 1D Learning

The purpose and goal of this assignment was to design and implement a small system to predict a class of a single numerical variable in a binomial class problem. In order to do this, it was requested to implement or to think of one or more “1D classifiers”, discussing their computational complexities in the learning phases, the performances on the given dataset, the differences and similarities with related or alternative methods. This report is structured as follows: before describing the classifiers and the implementation details, there will be an introduction to the suggested dataset in order to understand some of the choices that have been made during the design and implementation phases. Together with some of the theory that lies behind the implemented classifiers, the implementation choices and details will be discussed. The evaluation session will show some of the results obtained by the classifiers on the features of the dataset, comparing their performance and trying to understand the reasons behind their success or their failure. Together with the meaning of the classifiers’ evaluation, a more detailed discussion about the relation between the dataset and the classifiers over the assigned task will follow in the pertinent “Discussion” session, which will lead to the conclusions drawn from this assignment.