Stats 202 - Lecture 1

Descriptive methods find human interpretable patterns

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

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 http://cran.r-project.org/ 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 http://sites.google.com/site/stats202/data/weblog2.txt 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...
View Full Document

Ask a homework question - tutors are online