PPT-Data Mining Cluster Analysis: Basic Concepts

and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining by Tan Steinbach Kumar Introduction to Data Mining 2nd Edition Tan Steinbach Karpatne Kumar What is Cluster Analysis. 7. th. December. 2010. Elma . Akand. *, Mike Bain, Mark Temple. *CSE, . UNSW/School . of Biomedical and Health . Sciences,UWS. 1. The Sixth Australasian Ontology Workshop, . Adelaide . University of South Australia. 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. Another Introduction to Data Mining. Course Information. 2. Knowledge Discovery in Data [and Data Mining] (KDD). Let us find something interesting!. Definition. := . “KDD is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data” . Chapter 10. . Cluster Analysis: Basic Concepts and . Methods. Jiawei Han, Computer Science, Univ. Illinois at Urbana-Champaign, 2106. 1. Chapter 10. . Cluster Analysis: Basic Concepts and Methods. Cluster Analysis: An Introduction. . . Chong Ho Yu. Why do we look at . grouping (cluster) patterns?. This regression model yields 21% variance explained.. The . p. value is not significant (p=0.0598). But remember we must look at (visualize) the data pattern rather than reporting the numbers. and Algorithms. From . Introduction to Data Mining. By Tan. , Steinbach, Kumar. Association Rule Mining. Given a set of transactions, find rules that will predict the occurrence of an item based on the occurrences of other items in the transaction. Microsoft Enterprise Consortium. Prepared by David Douglas, University of Arkansas. Hosted by the University of Arkansas. Prepared by David Douglas, University of Arkansas. 2. What is Data Mining?. Knowledge Discovery. Chong Ho Yu. Crime hot spots. How can criminologists find the hot spots?. Data reduction. Group variables into factors or components based on people’s response patterns. PCA. Factor analysis. Group people into groups or clusters based on variable patterns. Ruizhu. Yang. 04/25/2014. References. Otari. G V, . Kulkarni. R V. A Review of Application of Data Mining in Earthquake Prediction[J]. . 2012.. Dzwinel. . W, Yuen D A, . Boryczko. K, et al. Cluster analysis, data-mining, multi-dimensional visualization of earthquakes over space, time and feature space[C]//Nonlinear Proc. in . 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. Hadoop/Cascading/Bixo in EC2 Ken Krugler, Bixo Labs, Inc. ACM Data Mining SIG 08 December 2009 About me u Background in vertical web crawl – Krugle search engine for open source code – Bixo open s By. Shailaja K.P. Introduction. Imagine that you are a sales manager at . AllElectronics. , and you are talking to a customer who recently bought a PC and a digital camera from the store. . What should you recommend to her next? . Hierarchical clustering. Density-based clustering. Cluster validity. Clustering topics. Proximity. is a generic term that refers to either similarity or dissimilarity.. Similarity. Numerical measure of how . Prepared by David Douglas, University of Arkansas. Hosted by the University of Arkansas. 1. IBM . Clustering. Hosted by the University of Arkansas. 2. Quick Refresher. . DM used to find previously unknown meaningful patterns in data.