What This Document Is
This document contains sample solutions for the Week One homework assignment in ISYE 6501, Intro Analytics Modeling at Georgia Tech. It’s designed to supplement the course material and provide students with different approaches to solving the assigned problems.
Why This Document Matters
This resource is valuable for students enrolled in ISYE 6501 who are seeking to check their understanding of the initial concepts and problem-solving techniques covered in the first week. It’s particularly helpful for identifying alternative methods and exploring optional extensions to the homework questions. The document emphasizes learning and skill development as the primary goals of the assignments.
Common Limitations or Challenges
This document provides *solutions* but does not offer detailed explanations of the underlying concepts. It assumes a base level of understanding from lectures and readings. It’s intended as a learning aid, not a replacement for actively working through the problems yourself. It doesn’t cover all possible solution paths, focusing instead on illustrative examples.
What This Document Provides
The full document includes:
* Sample solutions to Question 2.1, which asks students to identify a classification problem and potential predictors.
* Detailed guidance and code examples for Question 2.2, involving the use of the `ksvm` function in R to build a classifier for credit card application data. This includes instructions on scaling data, setting the `C` parameter, and interpreting the model’s output.
* Notes on the `ksvm` function and its parameters.
* A link to the original Credit Approval Data Set from the UCI Machine Learning Repository.
This preview does *not* include the complete code, the full solutions to all possible approaches, or a detailed explanation of the statistical theory behind the methods used.