Towards UCI plus : A mindful repository design

作     者：Macia, Nuria Bernado-Mansilla, Ester 

作者机构：La Salle Univ Ramon Llull Grp Recerca Sistemes Intelligents Barcelona 08022 Spain 

出 版 物：《INFORMATION SCIENCES》 (信息科学)

年 卷 期：2014年第261卷

页      面：237-262页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Ministerio de Educacion y Ciencia [TIN2008-06681-C06-05] Fundacio Credit Andorra Govern d'Andorra 

主　　题：Data repository Data complexity Classification Synthetic data set 

摘      要：Public repositories have contributed to the maturation of experimental methodology in machine learning. Publicly available data sets have allowed researchers to empirically assess their learners and, jointly with open source machine learning software, they have favoured the emergence of comparative analyses of learners performance over a common framework. These studies have brought standard procedures to evaluate machine learning techniques. However, current claims such as the superiority of enhanced algorithms are biased by unsustained assumptions made throughout some praxes. In this paper, the early steps of the methodology, which refer to data set selection, are inspected. Particularly, the exploitation of the most popular data repository in machine learning the UCI repository is examined. We analyse the type, complexity, and use of UCI data sets. The study recommends the design of a mindful data repository, UCI+, which should include a set of properly characterised data sets consisting of a complete and representative sample of real-world problems, enriched with artificial benchmarks. The ultimate goal of the UCI+ is to lay the foundations towards a well-supported methodology for learner assessment. (C) 2013 Elsevier Inc. All rights reserved.