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

机译:估算数据挖掘项目工作量的成本模型(DMCoMo)

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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 (DMCoMo). The drivers of the model will be proposed first and later the equation of the model will be proposed.
机译:CRISP-DM是开发数据挖掘项目的标准。 CRISP-DM提出了开发数据挖掘项目时必须执行的流程和任务。 CRISP-DM提出的任务是数据挖掘项目的成本估算。在软件开发中,描述了许多估算项目开发成本的方法(SLIM,SEER-SEM,PRICE-S和COCOMO)。这些方法不适用于Data Mining项目,因为在Data Mining中,软件开发不是首要目标。已经提出了一些方法来估计数据挖掘项目的某些阶段,但是没有方法来估计通用数据挖掘项目的全球成本。缺乏数据挖掘项目估算方法的原因是,由于项目开始时的不现实估算,导致许多实际项目失败。因此,在本文中,我们建议为数据挖掘项目(DMCoMo)设计和验证类似于软件开发中的COCOMO或SLIM的参数成本估算模型。将首先提出模型的驱动因素,然后提出模型方程。

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