Advanced Computing Seminar Data Mining and Its Industrial Applications Chapter 9 Data Mining tools

Feb 25, 2014

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2014-2-25. Chap 9 Data Mining tools Zhongzi Shi. 2. Outline. IntroductionSASSPSS Intelligent Miner(IBM)MSMiner Summary. 2014-2-25. Chap 9 Data Mining tools Zhongzi Shi. 3. Data Mining Tasks. ClassificationClusteringClass ProbabilityAssociation or Affinity GroupingDescription and Visualizati

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Advanced Computing Seminar Data Mining and Its Industrial Applications Chapter 9 Data Mining tools

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Data Mining Tools

Data Mining Tools. DBminer Technology Inc.: DBMiner 2.0 ( http://www.dbminer.com/ ) Megaputer Intelligence: PolyAnalyst 4.6 ( http://www.megaputer.com/ ) Microsoft SQL Server 2000: Analysis Services ( http://www.microsoft.com/sql/ )

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Data Mining Research and Applications

Data Mining Research and Applications. Workshop on Cyberinfrastructure For Environmental Research and Education October 31, 2002 Steve Tanner Information Technology and Systems Center University of Alabama in Huntsville stanner@itsc.uah.edu 256.824.5143 www.itsc.uah.edu. Key Questions:.

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Data Mining : Commercial Applications

Data Mining : Commercial Applications . 趙民德中央研究院統計科學研究所 2002/10/28. DM  good data analysis KDD  DM with commercial objective in mind. Data mining for maximum value is difficult unless a structured plan is followed. Knowledge Discovery process to get the most out of data mining. .

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Data Mining Tools

Data Mining Tools. Overview & Tutorial Ahmed Sameh Prince Sultan University Department of Computer Science & Info Sys May 2010 (Some slides belong to IBM). Introduction Outline. Goal: Provide an overview of data mining. Define data mining Data mining vs. databases

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DATA MINING LECTURE 9

DATA MINING LECTURE 9. Classification Decision Trees Evaluation. Illustrating Classification Task. Examples of Classification Task. Predicting tumor cells as benign or malignant Classifying credit card transactions as legitimate or fraudulent

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Data Mining Chapter 9 Moving on: Applications and Beyond

Data Mining Chapter 9 Moving on: Applications and Beyond. Kirk Scott. So-called machine learning is a broad topic with many ramifications Data mining is just an applied subset of this overall field

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DATA MINING LECTURE 9

DATA MINING LECTURE 9. Classification Basic Concepts Decision Trees. What is classification?. Tax-return data. categorical. categorical. continuous. class. What is classification?.

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Data Mining Tools

Data Mining Tools. A crash course C. Faloutsos. Subset of:. www.cs.cmu.edu/~christos/TALKS/ SIGMETRICS03-tut/. High-level Outline. [I - Traditional Data Mining tools classification, CART trees; clustering II - Time series: analysis and forecasting ARIMA; Fourier, Wavelets]

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Data mining: theory and applications

Data mining: theory and applications. Heikki Mannila. Data Mining: Theory and Applications. Data analysis becoming more important in other sciences and in industry New measurement methods Ability to store data High-dimensional large data sets

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Grid Computing in Data Mining and Data Mining on Grid Computing

Grid Computing in Data Mining and Data Mining on Grid Computing. David Cieslak ( dcieslak@cse.nd.edu ) Advisor: Nitesh Chawla (nchawla@cse.nd.edu) University of Notre Dame. Grid Computing in Data Mining. How you help me. Data Mining Primer.

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Data Mining: Applications

Data Mining: Applications. Dr. Hany Saleeb. Applications and Trends in Data Mining. Data mining applications Data mining system products and research prototypes Additional themes on data mining Social impact of data mining Trends in data mining Summary. Data Mining Applications.

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Business Data Mining Applications

Business Data Mining Applications. Business Data Mining Applications. Partial representative sample of applications Catalog sales CRM Credit scoring Banking (loans) Investment risk Insurance. Fingerhut. Founded 1948 today sends out 130 different catalogs to over 65 million customers

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Data Mining: Applications

Data Mining: Applications. Applications and Trends in Data Mining. Data mining applications Data mining system products and research prototypes Additional themes on data mining Social impact of data mining Trends in data mining Summary. Data Mining Applications.

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Top Data Mining Tools

It is rightfully said that data is money in today's world. Along with the transition to an app-based world comes the exponential growth of data. Orange, Weka,Rattle GUI, Apache Mahout, SCaViS, RapidMiner, R, ML-Flex, Databionic ESOM Tools, Natural Language Toolkit, SenticNet API , ELKI , UIMA, KNIME, Chemicalize.org , Vowpal Wabbit, GNU Octave, CMSR Data Miner, Mlpy, MALLET, Shogun, Scikit-learn, LIBSVM, LIBLINEAR, Lattice Miner, Dlib, Jubatus, KEEL and more

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Advanced Computing Seminar Data Mining and Its Industrial Applications — Chapter 7 — Fuzzy Sets

Advanced Computing Seminar Data Mining and Its Industrial Applications — Chapter 7 — Fuzzy Sets. Zhongzhi Shi, Markus Stumptner, Yalei Hao, Gerald Quirchmayr Knowledge and Software Engineering Lab Advanced Computing Research Centre School of Computer and Information Science

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Data Mining: Applications

543 views • 49 slides

Data Mining and Its Applications

Data Mining and Its Applications. Data Mining Techniques – For Marketing, Sales, and Customer Support , by Michael J.A. Berry and Gordon Linoff, John Wiley & Sons, Inc., 1997.

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Grid Computing in Data Mining and Data Mining on Grid Computing

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