NDLI logo
  • Content
  • Similar Resources
  • Metadata
  • Cite This
  • Log-in
  • Fullscreen
Log-in
Do not have an account? Register Now
Forgot your password? Account recovery
  1. Proceedings of the KDD-09 Workshop on Statistical and Relational Learning in Bioinformatics (StReBio '09)
  2. Multi-class protein fold recognition using large margin logic based divide and conquer learning
Loading...

Please wait, while we are loading the content...

Using random forests to uncover bivariate interactions in high dimensional small data sets
Identification of structurally important amino acids in proteins by graph-theoretic measures
Lift-based search for significant dependencies in dense data sets
Finding optimal parameters for edit distance based sequence classification is NP-hard
Multi-class protein fold recognition using large margin logic based divide and conquer learning
Protein sequence alignment and structural disorder: a substitution matrix for an extended alphabet
Handling missing values and censored data in PCA of pharmacological matrices
Comparing graph-based representations of protein for mining purposes
Can we improve on the identification of transcription factor binding sites?

Similar Documents

...
Multi-class protein fold recognition using large margin logic based divide and conquer learning.

Article

...
Multi-Class protein fold recognition using large margin logic based divide and conquer learning

Article

...
Multi-class fuzzy support vector machine based on dismissing margin

Article

...
Divide-and-Conquer Large-Scale Support Vector Classification (2006)

...
Close-class-set discrimination method for large-class-set pattern recognition using support vector machines

Article

...
An Efficient Algorithm for Multi-class Support Vector Machines

Article

...
Multi-Class Protein Subcellular Localization Prediction using Support Vector Machines

Article

...
Unsupervised and Semi-Supervised Two-class Support Vector Machines

Article

...
An Approach to Large Margin Design of Prototype-Based Pattern Classifiers

Article

Multi-class protein fold recognition using large margin logic based divide and conquer learning

Content Provider ACM Digital Library
Author Lodhi, Huma Muggleton, Stephen Sternberg, Mike J. E.
Abstract Inductive Logic Programming (ILP) systems have been successfully applied to solve complex biological problem by viewing them as binary classification tasks. It remains an open question how an accurate solution to a multi-class problem can be obtained by using a logic based learning method. In this paper we present a novel logic based approach to solve complex and challenging multi-class classification problems in bioinformatics by focusing on a particular task, namely protein fold recognition. Our technique is based on the use of large margin kernel-based methods in conjunction with first order rules induced by an ILP system. The proposed approach learns a multi-class classifier by using a divide and conquer reduction strategy that splits multi-classes into binary groups and solves each individual problem recursively hence generating an underlying decision list structure. The method is applied to assigning protein domains to folds. Experimental evaluation of the method demonstrates the efficacy of the proposed approach to solving complex multi-class classification problems in bioinformatics.
Starting Page 22
Ending Page 26
Page Count 5
File Format PDF
ISBN 9781605586670
DOI 10.1145/1562090.1562095
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2009-06-28
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Support vector machines Evaluation Multi-class classification Support vector inductive logic programming Inductive logic programming Protein fold recognition Bioinformatics
Content Type Text
Resource Type Article
  • About
  • Disclaimer
  • Feedback
  • Sponsor
  • Contact
  • Chat with Us
About National Digital Library of India (NDLI)
NDLI logo

National Digital Library of India (NDLI) is a virtual repository of learning resources which is not just a repository with search/browse facilities but provides a host of services for the learner community. It is sponsored and mentored by Ministry of Education, Government of India, through its National Mission on Education through Information and Communication Technology (NMEICT). Filtered and federated searching is employed to facilitate focused searching so that learners can find the right resource with least effort and in minimum time. NDLI provides user group-specific services such as Examination Preparatory for School and College students and job aspirants. Services for Researchers and general learners are also provided. NDLI is designed to hold content of any language and provides interface support for 10 most widely used Indian languages. It is built to provide support for all academic levels including researchers and life-long learners, all disciplines, all popular forms of access devices and differently-abled learners. It is designed to enable people to learn and prepare from best practices from all over the world and to facilitate researchers to perform inter-linked exploration from multiple sources. It is developed, operated and maintained from Indian Institute of Technology Kharagpur.

Learn more about this project from here.

Disclaimer

NDLI is a conglomeration of freely available or institutionally contributed or donated or publisher managed contents. Almost all these contents are hosted and accessed from respective sources. The responsibility for authenticity, relevance, completeness, accuracy, reliability and suitability of these contents rests with the respective organization and NDLI has no responsibility or liability for these. Every effort is made to keep the NDLI portal up and running smoothly unless there are some unavoidable technical issues.

Feedback

      Sponsor

      Ministry of Education, through its National Mission on Education through Information and Communication Technology (NMEICT), has sponsored and funded the National Digital Library of India (NDLI) project.

      Contact National Digital Library of India
      Central Library (ISO-9001:2015 Certified)
      Indian Institute of Technology Kharagpur
      Kharagpur, West Bengal, India | PIN - 721302
      See location in the Map
      03222 282435
      Mail: support@ndl.gov.in
      Sl. Authority Responsibilities Communication Details
      1 Ministry of Education (GoI),
      Department of Higher Education
      Sanctioning Authority https://www.education.gov.in/ict-initiatives
      2 Indian Institute of Technology Kharagpur Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project https://www.iitkgp.ac.in
      3 National Digital Library of India Office, Indian Institute of Technology Kharagpur The administrative and infrastructural headquarters of the project Dr. B. Sutradhar  bsutra@ndl.gov.in
      4 Project PI / Joint PI Principal Investigator and Joint Principal Investigators of the project Dr. B. Sutradhar  bsutra@ndl.gov.in
      Prof. Saswat Chakrabarti  will be added soon
      5 Website/Portal (Helpdesk) Queries regarding NDLI and its services support@ndl.gov.in
      6 Contents and Copyright Issues Queries related to content curation and copyright issues content@ndl.gov.in
      7 National Digital Library of India Club (NDLI Club) Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach clubsupport@ndl.gov.in
      8 Digital Preservation Centre (DPC) Assistance with digitizing and archiving copyright-free printed books dpc@ndl.gov.in
      9 IDR Setup or Support Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops idr@ndl.gov.in
      I will try my best to help you...
      Cite this Content
      Loading...