Stats 202 - Lecture 1

Descriptive methods find human interpretable patterns

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Unformatted text preview: ture values of other variables. Descriptive Methods: Find human-interpretable patterns that describe the data. Examples of Data Mining Tasks Classification [Predictive] (Chapters 4,5) ●Regression [Predictive] (covered in stats classes) ● Visualization [Descriptive] (in Chapter 3) ●Association Analysis [Descriptive] (Chapter 6) ●Clustering [Descriptive] (Chapter 8) ●Anomaly Detection [Descriptive] (Chapter 10) ● Software We Will Use: R Can be downloaded from for Windows, Mac or Linux Downloading R for Windows: Downloading R for Windows: Downloading R for Windows: Introduction to Data Mining by Tan, Steinbach, Kumar Chapter 2: Data What is Data? An attribute is a property or characteristic of an object Examples: eye color of a person, temperature, etc. Objects An Attribute is also known as variable, field, characteristic, or feature A collection of attributes describe an object An object is also known as record, point, case, sample, entity, instance, or observation Attributes Reading Data into R Download it from the web at What is your working directory? > getwd() Change it to your deskop: > setwd("/Users/rajan/Desktop") Read it in: > data<-read.csv("weblog2.txt", sep=" ",header=F) Reading Data in...
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This note was uploaded on 02/03/2014 for the course STATS 202 taught by Professor Taylor during the Fall '09 term at Stanford.

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