U.S. flag
      An official website of the United States government, Department of Justice.
        Here's how you know
      Here's how you know**Official websites use .gov**
            
            A **.gov** website belongs to an official government organization in the United States.
      **Secure .gov websites use HTTPS**
            
            A **lock** (
            A locked padlock
            ) or **https://** means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites. Menu

      
        close

            
            
                                              About NIJ
        
                    
  
          About NIJ
      
    
          The NIJ Director
          How NIJ Is Organized
          Mission and Guiding Principles
          Research and Development Process
          Strategic Framework
          Assessments of NIJ
          Annual Reports & Reports to Congress
          Staff Directory
          Funding & Awards
        
                    
  
          Funding & Awards
      
    
          Current Funding
          Forthcoming Funding
          Expired Funding
          Awards: Listing of Funded Projects
          Guidance for Applicants and Awardees
          Fellowship & Student Programs
          Travel Scholarships
          NIJ Challenge Program
          Library & Multimedia
        
                    
  
          Library & Multimedia
      
    
          NIJ Journal
          Podcasts
          Publications Listing
          Multimedia Listing
          Rated Practices on CrimeSolutions
          Rated Programs on CrimeSolutions
          Software & Databases
          Datasets
          Patents
          Topics
        
                    
  
          Topics
      
    
          Article Listing
          Corrections
          Courts
          Crime Prevention
          Crimes
          Drugs and Crime
          Equipment and Technology
          Forensic Sciences
          Youth Justice
          Justice System Reform
          Law Enforcement
          Tribal Crime and Justice
          Victims of Crime
          Events
        
                    
  
          Events
      
    
          NIJ 2024 Research Conference
          Scheduled Events
          On-Demand Events
          Research Meetings & Workshops
          NIJ-Hosted Online Training

                            
                                About
          Contact Us
          Subscribe
          Topics A-Z
                  Share
FacebookXLinkedInRedditPinterestEmail Home
                            Library & Multimedia
 Regularization-based learning of the Choquet integral
NCJ Number
              308325

Author(s)
          D. T. Anderson;
                        S. R. Price;
                        T. C. Havens
Date Published

2014
Length
              8 pages
Annotation
              In this paper, the authors discuss a regularization approach to learning the fuzzy measure for the Choquet fuzzy integral; discuss the mathematical motivation for such an approach, as well as its applicability, impact, and desirable properties; and show that it is possible to reduce the effect of overfitting as well as to force the learning of fewer numbers of sources.
Abstract
              A number of data-driven fuzzy measure (FM) learning techniques have been put forth for the fuzzy integral (FI). Examples include quadratic programming, Gibbs sampling, gradient descent, reward and punishment and evolutionary optimization. However, most approaches focus solely on the minimization of the sum of squared error (SSE). Limited attention has been placed on characterizing and subsequently minimizing model (i.e., FM) complexity. Furthermore, the vast majority of learning techniques are highly susceptible to over-fitting and noise. Herein, the authors explore a regularization approach to learning the FM for the Choquet FI. They investigate the mathematical motivation for such an approach, its applicability and impact on different types of FMs, and its desirable properties for quadratic programming (QP) based optimization. The authors show that L\ regularization has a distinct meaning for measure learning and aggregation operators. Experiments are performed and validated with respect to the Shapley index. Specifically, they show that it is possible to reduce the effect of overfitting, and they can identify higher quality measures and, if desired, force the learning of fewer numbers of sources. (Published Abstracts Provided)
      
  
          Additional Details
Grant Number(s)
        2011-DN-BX-K838


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)


  
  
        
  Award
        Graphical User Interface for a Multi-Factorial Age-At-Death Estimation Method Using Fuzzy Integrals
    
  
  
Date Published: January 1, 2014
    
          Downloads
        
                      HTML

Side navigation
  

        

  
  
              NIJ Journal
    
      
            
            
            
      Podcasts
    
      
            
            
            
      Publications Listing
    
      
            
            
            
      Multimedia Listing
    
      
            
            
            
      Rated Practices on CrimeSolutions
    
      
            
            
            
      Rated Programs on CrimeSolutions
    
      
            
            
            
      Software & Databases
    
      
            
            
            
      Datasets
    
      
            
            
            
      PatentsRelated Topics
        
                Forensic sciences
        Research and development
        Evaluation



  
Similar Publications
        
                      Near-infrared Excitation Raman Analysis of Underlying Colorants on Redyed Fabric
                  Moving Forward While Looking Back: Understanding the Influence of a “Test All” SAK Mandate on Sexual Assault Case Attrition
                  What Medical Examiner’s And Coroner’s Offices Should Know About Molecular Autopsy
 Top

      National Institute of Justice

        
        
                        About NIJ
                    About NIJ
      
    
                  How NIJ Is Organized
      
    
                  NIJ Director
      
    
                  Research Disclaimer
      
    
                  Funding & Awards
                    Funding & Awards Home
      
    
                  Awards Listing
      
    
                  Current Funding
      
    
                  Guidance for Applicants and Awardees
      
    
                  Resources
                    Events
      
    
                  Podcasts
      
    
                  Publications
      
    
                  Topics
      
    
                  Multimedia
      
    
                  Reuse Policy
      
    
                  Contacts
                    Contact NIJ
      
    
                  Staff Directory
      
    
                  Submit a FOIA Request
      
    
                  File a Civil Rights ComplaintFacebook
          
                      X
          
                      YouTube
  

      810 7th St. NW, Washington, D.C. 20531
      
              Secondary Footer link menu
            Accessibility
              Plain Language
              Privacy Policy
              Legal Policies and Disclaimer
              No FEAR Act
              Freedom of Information Act
              USA.gov
              Justice.gov