Cantitate/Preț
Produs
Total produse
Vezi coșul
Gentle Introduction to Support Vector Machines in Biomedicine, a - Volume 2: Case Studies and Benchmarks de Alexander Statnikov

Gentle Introduction to Support Vector Machines in Biomedicine, a - Volume 2: Case Studies and Benchmarks

Autor Alexander Statnikov, Constantin F. Aliferis, Douglas P. Hardin
en Limba Engleză Hardback – 30 iun 2012
Support Vector Machines (SVMs) are among the important developments in pattern recognition and statistical machine learning. This book introduces SVMs and their extensions and allows biomedical researchers to understand and apply them in real-life research in a very easy manner.
Citește tot Restrânge

Preț: 45087 lei

Preț vechi: 56359 lei
-20% Nou

Puncte Express: 676
Preț estimativ în valută:
8629€ • 9011$ • 7154£

Carte indisponibilă temporar


Wish list
Gift list
Am citit!
Adaugă în listă
Doresc să fiu notificat când acest titlu va fi disponibil:
Trimite
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9789814324397
ISBN-10: 9814324396
Pagini: 212
Dimensiuni: 198 x 22 x 236 mm
Greutate: 0 kg
Editura: WORLD SCIENTIFIC

Cuprins

Preliminaries: Introduction and Book Overview; Methods Used in this Book; Case Studies and Comparative Evaluation in High-Throughput Genomic Data: Application and Comparison of SVMs and Other Methods for Multicategory Microarray-Based Cancer Classification; Comparison of SVMs and Random Forests for Microarray-Based Cancer Classification; Comparison of SVMs and Kernel Ridge Regression for Microarray-Based Cancer Classification (Contributed by Zhiguo Li); Application and Comparison of SVMs and Other Methods for Multicategory Classification in Microbiomics (Contributed by Mikael Henaff, Kranti Konganti, Varun Narendra, Alexander V Alekseyenko); Application to Assessment of Plasma Proteome Stability; Case Studies and Comparative Evaluation in Text Data: Application and Comparison of SVMs and Other Methods for Retrieving High-Quality Content-Specific Articles (Contributed by Yindalon Aphinyanaphongs); Application and Comparison of SVMs and Other Methods for Identifying Unproven Cancer Treatments on the Web (Contributed by Yindalon Aphinyanaphongs); Application to Predicting Future Article Citations (Contributed by Lawrence Fu); Application to Classifying Instrumentality of Article Citations (Contributed by Lawrence Fu); Application and Comparison of SVMs and Other Methods for Identifying Drug - Drug Interactions-Related Literature (Contributed by Stephany Duda); Case Studies with Clinical Data: Application to Predicting Clinical Laboratory Values; Application to Modeling Clinical Judgment and Guideline Compliance in the Diagnosis of Melanoma (Contributed by Andrea Sboner); Other Comparative Evaluation Studies of Broad Applicability: Using SVMs for Causal Variable Selection; Application and Comparison of SVM-RFE and GLL Methods.