Skip to content

Booksellers & Trade Customers: Sign up for online bulk buying at trade.atlanticbooks.com for wholesale discounts

Booksellers: Create Account on our B2B Portal for wholesale discounts

Applied Genetic Programming and Machine Learning

by Hitoshi Iba , Yoshihiko Hasegawa , Topon Kumar Paul
Save 17% Save 17%
Current price ₹22,957.00
Original price ₹27,549.00
Original price ₹27,549.00
Original price ₹27,549.00
(-17%)
₹22,957.00
Current price ₹22,957.00

Imported Edition - Ships in 18-21 Days

Free Shipping in India on orders above Rs. 500

Request Bulk Quantity Quote
+91
Book cover type: Hardcover
  • ISBN13: 9781439803691
  • Binding: Hardcover
  • Subject: N/A
  • Publisher: CRC Press
  • Publisher Imprint: CRC Press
  • Publication Date:
  • Pages: 354
  • Original Price: USD 225.0
  • Language: English
  • Edition: 1
  • Item Weight: 640 grams
  • BISAC Subject(s): Data Science / Data Analytics

What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic programming and machine learning techniques. Written by leaders in this field, Applied Genetic Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications.

Reflecting rapidly developing concepts and emerging paradigms, this book outlines how to use machine learning techniques, make learning operators that efficiently sample a search space, navigate the search process through the design of objective fitness functions, and examine the search performance of the evolutionary system. It provides a methodology for integrating GP and machine learning techniques, establishing a robust evolutionary framework for addressing tasks from areas such as chaotic time-series prediction, system identification, financial forecasting, classification, and data mining.

The book provides a starting point for the research of extended GP frameworks with the integration of several machine learning schemes. Drawing on empirical studies taken from fields such as system identification, finanical engineering, and bio-informatics, it demonstrates how the proposed methodology can be useful in practical inductive problem solving.

Iba, Hitoshi; Hasegawa, Yoshihiko; Paul, Topon Kumar

Trusted for over 49 years

Family Owned Company

Secure Payment

All Major Credit Cards/Debit Cards/UPI & More Accepted

New & Authentic Products

India's Largest Distributor

Need Support?

Whatsapp Us