Paper Info
Title
Uninformed Methods to Build Optimal Choice-Based Ensembles.
Abstract
The paper explores uninformed methods to build ensembles using aggregations of single choice models. The research aims at developing new models to combine the performance of ensembles with the transparency of choice models. The dataset used to fit the models included rational, emotional and attentional features that were used as explanatory variables of user's choice. The results point out the superior performance of bagging methods to build optimal choice-based ensembles.
Year
DOI
Venue
2019
10.1007/978-3-030-19651-6_6
Lecture Notes in Computer Science
Keywords
Field
DocType
Recommender systems,Ensembles,Choice models,Decision-making
Recommender system,Transparency (graphic),Computer science,Artificial intelligence,Machine learning
Conference
Volume
ISSN
Citations 
11487
0302-9743
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Ameed Almomani101.01
Eduardo Sánchez Vila22912.82