✦ LIBER ✦

Rule Generation for Protein Secondary Structure Prediction With Support Vector Machines and Decision Tree

✍ Scribed by He, J.; Hu, H.-J.; Harrison, R.; Tai, P.C.; Pan, Y.

Book ID: 125832067
Publisher: IEEE
Year: 2006
Tongue: English
Weight: 576 KB
Volume: 5
Category: Article
ISSN: 1536-1241
DOI: 10.1109/TNB.2005.864021

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Cancer Diagnosis and Protein Secondary S

Cancer Diagnosis and Protein Secondary Structure Prediction Using Support Vector Machines

✍ Chu, F. ;Jin, G. ;Wang, L. 📂 Article 📅 2005 🏛 Springer Berlin Heidelberg ⚖ 736 KB

Prediction of backbone dihedral angles a

Prediction of backbone dihedral angles and protein secondary structure using support vector machines

✍ Petros Kountouris; Jonathan D Hirst 📂 Article 📅 2009 🏛 BioMed Central 🌐 English ⚖ 457 KB

Granular support vector machines with as

Granular support vector machines with association rules mining for protein homology prediction

✍ Yuchun Tang; Bo Jin; Yan-Qing Zhang 📂 Article 📅 2005 🏛 Elsevier Science 🌐 English ⚖ 620 KB

Knowledge Discovery in Bioinformatics ||

Knowledge Discovery in Bioinformatics || Current Methods for Protein Secondary-Structure Prediction Based on Support Vector Machines

✍ Hu, Xiaohua; Pan, Yi 📂 Article 📅 2007 🏛 John Wiley & Sons, Inc. 🌐 English ⚖ 505 KB

The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge research topics such as, gene expressions, protein/RNA structure prediction, phylogenetics, sequence and structural motifs, genomics and proteomics,

Granular Decision Tree and Evolutionary

Granular Decision Tree and Evolutionary Neural SVM for Protein Secondary Structure Prediction

✍ Reyaz-Ahmed, Anjum; Zhang, Yan-Qing; Harrison, Robert W. 📂 Article 📅 2009 🏛 Atlantis Press 🌐 English ⚖ 391 KB

[Studies in Computational Intelligence]

[Studies in Computational Intelligence] Rule Extraction from Support Vector Machines Volume 80 || Rule Extraction from SVM for Protein Structure Prediction

✍ Diederich, Joachim 📂 Article 📅 2008 🏛 Springer Berlin Heidelberg 🌐 English ⚖ 374 KB

Support vector machines (SVMs) are one of the most active research areas in machine learning. SVMs have shown good performance in a number of applications, including text and image classification. However, the learning capability of SVMs comes at a cost – an inherent inability to explain in a compre