Sign in to turn on 1-Click ordering.
Trade in Yours
For a 0.25 Gift Card
Trade in
More Buying Choices
Have one to sell? Sell yours here
Tell the Publisher!
Id like to read this book on Kindle

Don't have a Kindle? Get your Kindle here, or download a FREE Kindle Reading App.

Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (The Morgan Kaufmann Series in Data Management Systems) [Paperback]

Ian H. Witten
4.5 out of 5 stars  See all reviews (2 customer reviews)
RRP: 36.99
Price: 33.32 & FREE Delivery in the UK. Details
You Save: 3.67 (10%)
o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o
Temporarily out of stock.
Order now and we'll deliver when available. We'll e-mail you with an estimated delivery date as soon as we have more information. Your account will only be charged when we dispatch the item.
Dispatched from and sold by Amazon. Gift-wrap available.
‹  Return to Product Overview

Inside This Book (Learn More)
First Sentence
"What is meant by ""structural patterns""?" Read the first page
Browse Sample Pages
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Search inside this book:

Concordance (Learn More)
These are the most frequently used words in this book.
above  algorithm  another  attribute  best  between  called  case  chapter  class  classification  classifier  clusters  data  dataset  decision  described  difference  different  distribution  does  error  example  false  figure  file  filter  first  function  given  gives  good  however  humidity  information  instances  iris  learning  linear  machine  may  mean  measure  method  might  mining  missing  model  must  new  node  nominal  normal  number  numeric  often  ones  options  outlook  output  particular  performance  play  point  possible  prediction  probability  problem  process  rate  rather  result  rules  scheme  section  set  simple  situations  specify  split  standard  table  take  techniques  temperature  terms  test  time  training  tree  true  two  use  used  values  weight  weka  whether  work  yes 
‹  Return to Product Overview