A cost model to estimate the effort of data mining projects (DMCoMo)

被引:12
作者
Marban, Oscar [1 ]
Menasalvas, Ernestina [1 ]
Fernandez-Balzan, Covadonga [1 ]
机构
[1] Univ Politecn Madrid, Fac Informat, E-28660 Madrid, Spain
关键词
data mining; knowledge discovery; cost estimation; parametric model;
D O I
10.1016/j.is.2007.07.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
CRISP-DM is the standard to develop Data Mining projects. CRISP-DM proposes processes and tasks that you have to carry out to develop a Data Mining project. A task proposed by CRISP-DM is the cost estimation of the Data Mining project. In software development a lot of methods are described to estimate the costs of project development (SLIM, SEER-SEM, PRICE-S and COCOMO). These methods are not appropriate in the case of Data Mining projects because in Data Mining software development is not the first goal. Some methods have been proposed to estimate some phases of a Data Mining project, but there is no method to estimate the global cost of a generic Data Mining project. The lack of Data Mining project estimation methods is because of many real-life project failures due to the non-realistic estimation at the beginning of the projects. Consequently, in this paper we propose to design and validate a parametric cost estimation model, similar to COCOMO or SLIM in software development, for Data Mining projects (DMCoMo1). The drivers of the model will be proposed first and later the equation of the model will be proposed. (C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:133 / 150
页数:18
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