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.
['Alisson S. C. Alencar', 'Weslley L. Caldas', 'João Paulo Pordeus Gomes', 'Amauri H. de Souza', 'Paulo A. C. Aguilar', 'Cristiano Rodrigues', 'Wellington Franco', 'Miguel Franklin de Castro', 'Rossana M. C. Andrade']
MLM-rank: A Ranking Algorithm Based on the Minimal Learning Machine