CSCI 479 (Machine Learning) --- Lab 1

Objectives:

• Get familiar with selected machine learning platform
• Get familiar with tools performing data exploration
• Get familiar with data exploration

References:

• Introduction
• Data

Lab Task Description:

We must understand our data before we can use them effectively in machine learning process to build predictive models.

Data files usually have, but not limited to, the following formats: comma separated values (csv), Attribute-Relation File Format (arff), Excel (xlsx), and database relations.

There are many different tools that can assist with data exploration tasks. These tools can be categorized to the following types: machine learning platforms (such as Weka, etc.), RDMS (such as SQLite and Oracle, etc.), Spreadsheet Applications (such as Excel and OpenOffice Calc, etc.), and custom written software (such as your own programs).

Use Iris Data in csv format, Weather Data in arff format, and the assignment 1 dataset German Credit Data in xlsxformat as examples, practice using various tools to explore the data in these datasets. You can reference Assignment 1 to see what results we usually want to have when explore a dataset.