ITM 618 Study Guide - Midterm Guide: Rstudio, Business Intelligence, A124 Road

• School: Ryerson University
• Department: Information Technology Management
• Course: ITM 618
• Professor: Mehdi Kargar

Document Summary

The dataset (creditdata. csv) classifies customers as approved or not approved (i. e. , target class). The target class is in the 21st column and its name is approved . Value of 1 means approved and value of 2 means not approved. Number of attributes for classification: 20 (7 numerical, 13 categorical). The task should be developed using r (and in rstudio). 1- divide data into two datasets: 75% as training data, 25% as test data. Note: use this link to learn how to divide one dataset into training and test data: https://rpubs. com/id_tech/s1. 2- build a classification model based on the training data to predict if a new customer is approved or not: you can use regression or decision tree (or both to learn more! 3- test the model on the test data. 4- explain the model that you build and report its accuracy (precision). If you use decision tree, draw the tree. If you use regression, report the parameters and weight values.