PPT-MIS2502: Data Analytics Association Rule Mining

Association Rule Mining Examples of Association Rule Mining Market basket analysisaffinity analysis What products are bought together Where to place items on grocery store shelves Amazons recommendation engine. CS548 Xiufeng . Chen. S. ources. K. . Chitra. , . B.Subashini. , Customer Retention in Banking Sector using . Predictive . Data . Mining Technique. , International Conference on . Information . Technology, . November 5. th. , 2013. Parallel Association Rule Mining. Outline. Background of Association Rule Mining. Apriori Algorithm. Parallel Association Rule Mining. Count Distribution. Data Distribution. Candidate Distribution. Chapter 1. Kirk Scott. Iris . virginica. 2. Iris . versicolor. 3. Iris . setosa. 4. 1.1 Data Mining and Machine Learning. 5. Definition of Data Mining. The process of discovering patterns in data.. (The patterns discovered must be meaningful in that they lead to some advantage, usually an economic one.). Emre Eftelioglu. 1. What is Knowledge Discovery in Databases?. Data mining is actually one step of a larger process known as . knowledge discovery in databases. (KDD).. The KDD process model consists of six phases. Debapriyo Majumdar. Data Mining – Fall 2014. Indian Statistical Institute Kolkata. August 4 and 7, 2014. Transaction id. Items. 1. Bread, Ham, Juice,. Cheese, Salami, Lettuce. 2. Rice, . Dal, Coconut, Curry leaves, Coffee, Milk, Pickle. December 2013, Jakub Miarka, University of Leeds. RapidMiner. Formerly called . YALE. (Yet Another Language Environment). Environment for . machine learning, data and text mining, predictive and business analytics. Iris . virginica. 2. Iris . versicolor. 3. Iris . setosa. 4. 1.1 Data Mining and Machine Learning. 5. Definition of Data Mining. The process of discovering patterns in data.. (The patterns discovered must be meaningful in that they lead to some advantage, usually an economic one.). Iris . virginica. 2. Iris . versicolor. 3. Iris . setosa. 4. 1.1 Data Mining and Machine Learning. 5. Definition of Data Mining. The process of discovering patterns in data.. (The patterns discovered must be meaningful in that they lead to some advantage, usually an economic one.). is the use of:. data, . information technology, . statistical analysis, . quantitative methods, and . mathematical or computer-based models . to help managers gain improved insight about their business operations and . is the use of:. data, . information technology, . statistical analysis, . quantitative methods, and . mathematical or computer-based models . to help managers gain improved insight about their business operations and . Presented by: Ramoza Ahsan and Xiao Qin November 5 th , 2013 Parallel Association Rule Mining Outline Background of Association Rule Mining Apriori Algorithm Parallel Association Rule Mining Count Distribution MIS2502: Data Analytics Relational Data Modeling Acknowledgement: David Schuff Aaron Zhi Cheng http://community.mis.temple.edu/zcheng/ acheng@temple.edu Where we are… Transactional Database Analytical Data Store Global . and Local Association Rules. Abhishek Mukherji*. . Elke . A. . . Rundensteiner Matthew . O. . Ward. Department of Computer Science, Worcester Polytechnic Institute, MA, USA. Prepared by David Douglas, University of Arkansas. Hosted by the University of Arkansas. 1. IBM SPSS . Association Analysis. Also referred to as. Affinity Analysis. Market Basket Analysis. For MBA, basically means what is being purchased together.