MIS 2502 Study Guide - Final Guide: Data Mining, Cluster Analysis, Railways Act 1921

• School: Temple University
• Department: Management Information Systems
• Course: MIS 2502
• Professor: David Schuff

Document Summary

Mis data mining notes: data mining and data analytics techniques, explain the three data analytics techniques we covered in the course a. i. Determines probability of 2 events occurring together. a. i. 1. b. 2 columns; c1 is the transaction and c2 is what you bought. a. i. 1. c. Give it a list of transaction ids in products. a. i. 1. d. Ie: 1 product = 1 line; 10 products = 10 lines. a. i. 1. e. Ie: which products bought together, website most visited. a. i. 2. Ie: check characteristics and see how likely of them to payback, will they purchase or not? a. i. 2. c. Ie: whether to receive a loan, determine whether an investment will pay off. a. i. 2. d. Each line of data is characteristic of what you want to analyze. Each line is an observation of what you"re making a decision about. Unlike in cluster analysis, in decision trees you need the outcome. a. i. 3. Ie: grouping jeans by stores; fashion, stretch, leisure, original. a. i. 3. d.