-
- Australia
- Canada
- UK
- USA
- Afghanistan
- Albania
- Algeria
- American Samoa
- Andorra
- Angola
- Anguilla
- Antarctica
- Antigua and Barbuda
- Argentina
- Armenia
- Aruba
- Australia
- Austria
- Azerbaijan
- Bahamas
- Bahrain
- Bangladesh
- Barbados
- Belarus
- Belgium
- Belize
- Benin
- Bermuda
- Bhutan
- Bolivia
- Bosnia and Herzegovina
- Botswana
- Brazil
- British Indian Ocean Territory
- Brunei Darussalam
- Bulgaria
- Burkina Faso
- Burundi
- Cambodia
- Cameroon
- Canada
- Cape Verde
- Cayman
- Central African R
- Chad
- Chile
- China
- Cocos (Keeling)
- Colombia
- Comoros
- Congo, The DR
- Congo, Rep of
- Cook Is
- Costa Rica
- Cote d'Ivoire
- Croatia/Hrvatska
- Cuba
- Cyprus
- Czech Repu
- Denmark
- Djibouti
- Dominica
- Dominican R
- Timor-Leste
- Ecuador
- Egypt
- El Salvador
- Equatorial Guinea
- Eritrea
- Estonia
- Ethiopia
- Falklands (Malvinas)
- Fiji
- Finland
- France
- French Guiana
- French Polynesia
- French Southern Territories
- Gabon
- Gambia
- Georgia
- Germany
- Ghana
- Gibraltar
- Greece
- Greenland
- Grenada
- Guadeloupe
- Guam
- Guatemala
- Guernsey
- Guinea
- Guinea-Bissau
- Guyana
- Haiti
- Heard and McDonald Is
- Holy See (Vatican City State)
- Honduras
- Hong Kong
- Hungary
- Iceland
- India
- Indonesia
- Iran
- Iraq
- Ireland
- Isle of Man
- Israel
- Italy
- Jamaica
- Japan
- Jersey
- Jordan
- Kazakhstan
- Kenya
- Kiribati
- Korea, DPR
- Korea, Repub of
- Kuwait
- Kyrgyzstan
- Lao
- Latvia
- Lebanon
- Lesotho
- Liberia
- Libyan Arab Jamahiriya
- Liechtenstein
- Lithuania
- Luxembourg
- Montenegro
- Macau
- Macedonia
- Madagascar
- Malawi
- Malaysia
- Maldives
- Mali
- Malta
- Marshall Is
- Martinique
- Mauritania
- Mauritius
- Mayotte
- Mexico
- Micronesia, Federal State of
- Moldova
- Monaco
- Mongolia
- Montserrat
- Morocco
- Mozambique
- Myanmar
- Namibia
- Nauru
- Nepal
- Netherlands
- Netherlands Antilles
- New Caledonia
- New Zealand
- Nicaragua
- Niger
- Nigeria
- Niue
- Norway
- Oman
- Pakistan
- Palau
- Palestinian Territories
- Panama
- Papua New Guinea
- Paraguay
- Peru
- Philippines
- Pitcairn
- Poland
- Portugal
- Puerto Rico
- Qatar
- Reunion
- Romania
- Russian Federation
- Rwanda
- Serbia
- St Kitts and Nevis
- Snt Lucia
- Sa Vincent and the Grenadines
- San Marino
- Sao Tome and Principe
- Saudi Arabia
- Senegal
- Seychelles
- Sierra Leone
- Singapore
- Slovak R
- Slovenia
- Solomons
- Somalia
- South Africa
- South Georgia and the South Sandwich
- Spain
- Sri Lanka
- S Helena
- S Pierre and Miquelon
- Sudan
- Suriname
- Svalbard and Jan Mayen
- Swaziland
- Sweden
- Switzerland
- Syria
- Taiwan
- Tajikistan
- Tanzania
- Thailand
- Togo
- Tokelau
- Tonga
- Trinidad and Tobago
- Tunisia
- Turkey
- Turkmenistan
- Turks and Caicos
- Tuvalu
- Uganda
- Ukraine
- Unitd Arab Emirates
- UK
- USA
- Uruguay
- Uzbekistan
- Vanuatu
- Venezuela
- Vietnam
- Virgin Is, British
- Virgin Is, U.S.
- Wallis and Futuna
- Western Sahara
- Western Samoa
- Yemen
- Yugoslavia
- Zambia
- Zimbabwe
- Gift certificates
- Academic eBooks
- My account
- Help
- Wishlist
- Feedback
- Sign up
The Leading eBooks Store Online
for Kindle Fire, Apple, Android, Nook, Kobo, PC, Mac, Sony Reader...
Clustering for Data Mining
A Data Recovery Approach
US$ 109.95
(+ tax)
Preview (read now)
Add to my own site
Give this ebook to a friend
Add to my wishlist
Author's page
Publisher's page
Devices
- iPad
- PC
- e-readers with Adobe Digital Editions installed
- Mac
See the full list
Available Devices
X
This book is available for the following devices:
- iPad
- Windows
- Mac
- Sony Reader
- Cool-er Reader
- Nook
- Kobo Reader
- iRiver Story
File Formats
Download: secure PDF.
You can also read this book online in eb20 format without having to download anything.
You can also read this book online in eb20 format without having to download anything.
Permissions
Printing
Copy/Paste
Read Aloud
Printing
Copy/Paste
Read Aloud
more
Often considered more as an art than a science, the field of clustering has been dominated by learning through examples and by techniques chosen almost through trial-and-error. Even the most popular clustering methods--K-Means for partitioning the data set and Ward's method for hierarchical clustering--have lacked the theoretical attention that would establish a firm relationship between the two methods and relevant interpretation aids.Rather than the traditional set of ad hoc techniques, Clustering for Data Mining: A Data Recovery Approach presents a theory that not only closes gaps in K-Means and Ward methods, but also extends them into areas of current interest, such as clustering mixed scale data and incomplete clustering. The author suggests original methods for both cluster finding and cluster description, addresses related topics such as principal component analysis, contingency measures, and data visualization, and includes nearly 60 computational examples covering all stages of clustering, from data pre-processing to cluster validation and results interpretation.T his author's unique attention to data recovery methods, theory-based advice, pre- and post-processing issues that are beyond the scope of most texts, and clear, practical instructions for real-world data mining make this book ideally suited for virtually all purposes: for teaching, for self-study, and for professional reference.
less
Subject categories
- Academic > Mathematics > General > Mathematics
- Academic > Computer Science > Computer science
- Academic > Computer Science > Electronic data processing
- Academic > Computer Science > Computers - special aspects
- Academic > Computer Science > System design; Periodicals
- Academic > Computer Science > Database management
- Academic > Computer Science > Data mining
- Academic > Mathematics > Instruments and machines
- Academic > Mathematics > Geometry. Trigonometry.Topology
- Mathematics > Probability & Statistics
ISBNs
142003491X
9781420034912
9781584885344