chap1_intro - Data Mining: Introduction Lecture Notes for...

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© Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 1 Data Mining: Introduction Lecture Notes for Chapter 1 Introduction to Data Mining by Tan, Steinbach, Kumar
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© Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 2 Lots of data is being collected and warehoused Web data, e-commerce purchases at department/ grocery stores Bank/Credit Card transactions Computers have become cheaper and more powerful Competitive Pressure is Strong Provide better, customized services for an edge (e.g. in Customer Relationship Management) Why Mine Data? Commercial Viewpoint
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Why Mine Data? Scientific Viewpoint Data collected and stored at enormous speeds (GB/hour) remote sensors on a satellite telescopes scanning the skies microarrays generating gene expression data scientific simulations generating terabytes of data Traditional techniques infeasible for raw data Data mining may help scientists in classifying and segmenting data in Hypothesis Formation
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© Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 4 Mining Large Data Sets - Motivation There is often information “hidden” in the data that is not readily evident Human analysts may take weeks to discover useful information Much of the data is never analyzed at all 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 4,000,000 1995 1996 1997 1998 1999 The Data Gap Total new disk (TB) since 1995 Number of analysts From: R. Grossman, C. Kamath, V. Kumar, “Data Mining for Scientific and Engineering Applications”
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© Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 5 What is Data Mining? Many Definitions Non-trivial extraction of implicit, previously unknown and potentially useful information from data Exploration & analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns
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© Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 6 What is (not) Data Mining? What is Data Mining? Certain names are more prevalent in certain US locations (O’Brien, O’Rurke, O’Reilly… in Boston area) Group together similar documents returned by search engine according to their context (e.g. Amazon rainforest, Amazon.com,) What is not Data Mining? Look up phone number in phone directory Query a Web search engine for information about “Amazon”
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© Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 7 Draws ideas from machine learning/AI, pattern recognition, statistics, and database systems Traditional Techniques may be unsuitable due to Enormity of data High dimensionality of data Heterogeneous, distributed nature of data Origins of Data Mining Machine Learning/ Pattern Recognition Statistics/ AI Data Mining Database systems
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© Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 8 Data Mining Tasks Prediction Methods Use some variables to predict unknown or
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This note was uploaded on 01/29/2009 for the course CS 378 taught by Professor Dhillon during the Spring '09 term at University of Texas at Austin.

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chap1_intro - Data Mining: Introduction Lecture Notes for...

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