Program 2: Machine Learning

Due Date

This assignment is due at the beginning of the lecture on Thursday, March 11th.

Partners

You are required to work with one other person on this assignment. Please submit just one solution with both of your names on it.

Purpose

The purpose of this assignment is to introduce you to the Naive Bayes method, the k-nearest neighbors algorithm, and decision stumps augmented with AdaBoost.

Data Set

For this assignment, we will be using the automobile database. The .names file describes the data and the .data file provides the data.

Learning Techniques To Implement

Report

Write a professional report that includes the following sections:

  1. A description of your k-nearest neighbors algorithm and a report on its effectiveness. Use graphs and tables where appropriate.
  2. A description of your Naive Bayes method and a report on its effectiveness. Use graphs and tables where appropriate.
  3. A description of your decision stump (augmented with AdaBoost) algorithm and a report on its effectiveness. Use graphs and tables where appropriate.

General Requirements

What to Submit

  1. A printout of the source code that you produce.
  2. A printout of your program running in a representative fashion.
  3. The report.

Grading

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