Description: Further DetailsTitle: Machine Learning for Protein Subcellular Localization PredictionCondition: NewISBN-10: 1501510487EAN: 9781501510489ISBN: 9781501510489Publisher: De GruyterFormat: HardbackRelease Date: 04/24/2015Description: Comprehensively covers protein subcellular localization from single-label prediction to multi-label prediction, and includes prediction strategies for virus, plant, and eukaryote species. Three machine learning tools are introduced to improve classification refinement, feature extraction, and dimensionality reduction.Language: EnglishCountry/Region of Manufacture: USItem Height: 240mmItem Length: 170mmItem Weight: 495gAuthor: Shibiao Wan, Man-Wai MakGenre: Computing & InternetTopic: Science Nature & MathRelease Year: 2015 Missing Information?Please contact us if any details are missing and where possible we will add the information to our listing.
Price: 162.53 USD
Location: 60502
End Time: 2024-11-29T15:19:44.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money back or replacement (buyer's choice)
Return policy details:
Book Title: Machine Learning for Protein Subcellular Localization Prediction
Title: Machine Learning for Protein Subcellular Localization Prediction
ISBN-10: 1501510487
EAN: 9781501510489
ISBN: 9781501510489
Release Date: 04/24/2015
Release Year: 2015
Country/Region of Manufacture: US
Item Height: 240mm
Genre: Computing & Internet
Topic: Science Nature & Math
Number of Pages: 209 Pages
Language: English
Publication Name: Machine Learning for Protein Subcellular Localization Prediction
Publisher: DE Gruyter Gmbh, Walter
Publication Year: 2015
Subject: Signals & Signal Processing, Intelligence (Ai) & Semantics, Probability & Statistics / General, Data Processing, Databases / Data Mining
Item Weight: 17.5 Oz
Type: Textbook
Author: Man-Wai Mak, Shibiao Wan
Item Length: 9.4 in
Subject Area: Mathematics, Computers, Technology & Engineering
Item Width: 6.7 in
Format: Hardcover