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class04 - Concepts and Techniques Chapter 2 August29,2011

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August 29, 2011 Data Mining: Concepts and Techniques 1 Concepts and Techniques — Chapter 2 —
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August 29, 2011 Data Mining: Concepts and Techniques 2 General data characteristics Basic data description and exploration Measuring data similarity  What is about Data?
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August 29, 2011 Data Mining: Concepts and Techniques 3 What is Data? Collection of data objects and their  attributes An attribute is a property or  characteristic of an object Examples: eye color of a  person, temperature, etc. Attribute is also known as  variable, field, characteristic, or  feature A collection of attributes describe  an object Object is also known as record,  point, case, sample, entity, or  instance Tid Refund Marital Status Taxable Income Cheat 1 Yes Single 125K No 2 No Married 100K No 3 No Single 70K No 4 Yes Married 120K No 5 No Divorced 95K Yes 6 No Married 60K No 7 Yes Divorced 220K No 8 No Single 85K Yes 9 No Married 75K No 10 No Single 90K Yes Attributes Objects
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August 29, 2011 Data Mining: Concepts and Techniques 4 Important Characteristics of Structured Data Dimensionality Curse of dimensionality Sparsity Only presence counts Resolution Patterns depend on the scale   Similarity Distance measure
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August 29, 2011 Data Mining: Concepts and Techniques 5 Attribute Values Attribute values are numbers or symbols assigned to an attribute Distinction between attributes and attribute values Same attribute can be mapped to different attribute values  Example: height can be measured in feet or meters Different attributes can be mapped to the same set of  values  Example: Attribute values for ID and age are integers  But properties of attribute values can be different ID has no limit but age has a maximum and  minimum value
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August 29, 2011 Data Mining: Concepts and Techniques 6 Types of Attribute Values Nominal E.g., profession, ID numbers, eye color, zip codes Ordinal E.g., rankings (e.g., army, professions), grades, height  in {tall, medium, short} Binary E.g., medical test (positive vs. negative) Interval E.g., calendar dates, body temperatures  Ratio E.g., temperature in Kelvin, length, time, counts  
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August 29, 2011 Data Mining: Concepts and Techniques 7 Properties of Attribute Values The type of an attribute depends on which of the following properties it  possesses: Distinctness:   =   Order:   <  >   Addition:   +  -  Multiplication:  * / Nominal attribute: distinctness Ratio attribute: all 4 properties
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August 29, 2011 Data Mining: Concepts and Techniques
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class04 - Concepts and Techniques Chapter 2 August29,2011

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