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
Link To Document