• Menu
  • Skip to right header navigation
  • Skip to main content
  • Skip to secondary navigation
  • Skip to primary sidebar

OnlineProgrammingBooks.com

Legally Free Computer Books

  • All Categories
  • All Books
  • All Categories
  • All Books
  • About Us
  • Privacy policy
  • Disclaimer
  • Subscribe
  • Contact
You are here: Home ▶ Information Technology (IT) ▶ Data Mining: Desktop Survival Guide

Data Mining: Desktop Survival Guide

March 24, 2006

“Data Mining: Desktop Survival Guide” by Graham Williams is a free online book. Data mining is about building models from data. We build models to gain insights into the world and how the world works, so we can predict how things will behave into the future.

Book Description

A data miner, in building models, deploys many different data analysis and model building techniques. Our choices depend on the business problems to be solved. Although data mining is not the only approach it is becoming very widely used because it is well suited to the data environments we find in today’s enterprises. This is characterised by the volume of data available, commonly in the gigabytes and fast approaching the terabytes, and the complexity of that data, both in terms of the relationships that are awaiting discovery in the data and the data types available today, including text, image, audio, and video. Also, the business environments are rapidly changing, and analyses need to be regularly performed and models regularly updated to keep up with today’s dynamic world.

Table of Contents

  • The Business Problem
  • Data
  • Loading Data
  • Exploring Data
  • Interactive Graphics
  • Statistical Tests
  • Models
  • Network Analysis
  • Text Mining
  • Decision Trees
  • Random Forests
  • Boosting
  • Bootstrapping: Meta Algorithm
  • Bagging: Meta Algorithm
  • Support Vector Machine
  • Linear Regression
  • Neural Network
  • Naive Bayes
  • Survival Analysis
  • Evaluation and Deployment
  • Transforming Data
  • Deployment
  • Troubleshooting
  • Issues
  • Moving into R
  • R: The Language
  • Getting Help
  • Data
  • Graphics in R
  • Understanding Data
  • Preparing Data
  • Classification: Decision Trees
  • Classification: Boosting
  • Classification: Random Forests
  • Issues
  • Evaluating Models
  • Reporting
  • Fraud Analysis
  • Archetype Analysis

Download Free PDF / Read Online

Author(s): Graham Williams
Format(s): HTML
Link: Read online.

Similar Books:

  1. Data Mining and Knowledge Discovery in Real Life Applications
  2. Data Mining in Medical and Biological Research
  3. GNU/Linux Desktop Survival Guide
  4. Tools in Artificial Intelligence
  5. Student Survival Guide to Managing Group Projects
Previous Post: « Learning Perl the Hard Way
Next Post: Critical Information Infrastructure Protection and the Law »

Primary Sidebar

Get Latest Updates

  • Facebook
  • Pinterest
  • RSS
  • Twitter
  • YouTube
  • About Us
  • Privacy policy
  • Disclaimer
  • Subscribe
  • Contact

Copyright © 2006–2023 OnlineProgrammingBooks.com