Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning - Ivica Kopriva,Te-Ming Huang,Vojislav Kecman
-20% with code BOOKS
Shipping in 12-18 days
30-day return policy
"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory and the algorithms for mining huge data sets by using support vector machines (SVMs) in an iterative way. It demonstrates how kernel based SVMs can be used for dimensionality reduction (feature elimination) ... Full description
You May Also Like
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-20% with code BOOKS
In stock at our supplier
TOP
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All
Eliezer Yudkowsky, Nate Soares
-20% with code BOOKS
In stock at our supplier
TOP
AI Engineering: Building Applications with Foundation Models
-20% with code BOOKS
In stock at our supplier
TOP
Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI
-20% with code BOOKS
In stock at our supplier
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-20% with code BOOKS
In stock at our supplier
TOP
The Rust Programming Language
Steve Klabnik, Carol Nichols, Chris Krycho
-20% with code BOOKS
In stock at our supplier
TOP
How To Think About AI: A Guide For The Perplexed
-20% with code BOOKS
In stock at our supplier
TOP
Slanted 47 Digital Tools: Slanted Magazine
-20% with code BOOKS
In stock at our supplier
TOP
The Web Application Hacker's Handbook: Discovering and Exploiting Security Flaws
-20% with code BOOKS
In stock at our supplier
TOP
The Art of Game Design: A Book of Lenses
-20% with code BOOKS
In stock at our supplier
TOP
How Linux Works: What Every Superuser Should Know
-20% with code BOOKS
In stock at our supplier
TOP
Artificial Intelligence: A Modern Approach, Global Edition
-20% with code BOOKS
In stock at our supplier
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-20% with code BOOKS
In stock at our supplier
TOP
CompTIA Security+ Certification Kit: Exam SY0-701
-20% with code BOOKS
In stock at our supplier
TOP
Automate the Boring Stuff with Python
-20% with code BOOKS
In stock at our supplier
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-20% with code BOOKS
In stock at our supplier
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-20% with code BOOKS
In stock at our supplier
TOP
Hacking: The Art of Exploitation
-20% with code BOOKS
In stock at our supplier
TOP
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
-20% with code BOOKS
In stock at our supplier
TOP
HBR Guide to Generative AI for Managers
-20% with code BOOKS
In stock at our supplier
Description
"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory and the algorithms for mining huge data sets by using support vector machines (SVMs) in an iterative way. It demonstrates how kernel based SVMs can be used for dimensionality reduction (feature elimination) and shows the similarities and differences between the two most popular unsupervised techniques, the principal component analysis (PCA) and the independent component analysis (ICA). The book presents various examples, software, algorithmic solutions enabling the reader to develop their own codes for solving the problems. The book is accompanied by a website for downloading both data and software for huge data sets modeling in a supervised and semisupervised manner, as well as MATLAB based PCA and ICA routines for unsupervised learning. The book focuses on a broad range of machine learning algorithms and it is particularly aimed at students, scientists, and practicing researchers in bioinformatics (gene microarrays), text-categorization, numerals recognition, as well as in the images and audio signals de-mixing (blind source separation) areas.
More Information
| Author | Ivica Kopriva, Te-Ming Huang, Vojislav Kecman |
|---|---|
| Publisher | Springer Berlin Heidelberg |
| Series | Studies in Computational Intelligence |
| Release year | 2010 |
| Cover type | Softcover |
| EAN | 9783642068560 |