• DocumentCode
    3756508
  • Title

    MLM-rank: A Ranking Algorithm Based on the Minimal Learning Machine

  • Author

    Alisson S.C. Alencar;Weslley L. Caldas;Jo?o P.P. ;Amauri H. de Souza;Paulo A.C. Aguilar;Cristiano Rodrigues;Wellington Franco;Miguel F. de Castro;Rossana M.C. Andrade

  • Author_Institution
    Comput. Sci. Dept., Fed. Univ. of Ceara, Fortaleza, Brazil
  • fYear
    2015
  • Firstpage
    305
  • Lastpage
    309
  • Abstract
    Ranking is an important task in information retrieval and has gained much attention in recent years. Among the most used strategies, machine learning has achieved important results. The current work proposes a new machine learning based ranking algorithm, the MLM-RANK. MLM-RANK is based on the recently proposed Minimal Learning Machine (MLM). MLM is a supervised learning method that requires the adjustment of a single hyper parameter. The proposed method was evaluated against Prank and ELM Rank, both state of the art point wise ranking methods. In these tests MLM-RANK achieved promising results.
  • Keywords
    "Training","Estimation","Cost function","Mathematical model","Training data","Support vector machines","Supervised learning"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (BRACIS), 2015 Brazilian Conference on
  • Type

    conf

  • DOI
    10.1109/BRACIS.2015.39
  • Filename
    7424037