Classification of Signal Data Using Decision Trees

ABSTRACT
In this project, we propose the use of a decision tree as a method of classifying different signal data. Two specific types of signal data that we will attempt to classify are the scenic beauty values of forestry images and the pronunciations of proper nouns. Decision trees will be constructed for each set of the data using three decision tree algorithms: Bayesian, C4, and CART. Evaluations will be conducted on the two data sets using each of these three algorithms. A Graphical User Interface (GUI) will be implemented to demonstrate the performance of these algorithms.

A. Le, J. Ngan, and J. Shaffer Department of Electrical and Computer Engineering
Mississippi State University
email: {le, ngan, shaffer}@cavs.msstate.edu
URL: http://cavs.msstate.edu/research/isip/publications/courses/ece_4773/hse/ies/projects/group_dt/presentation/