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Data understanding phase implies collecting initial data, describing and exploring data.
Data understanding phase.
Data understanding phase Zan et al. (2007) stated that for this phase it is necessary to "determine what data is available to solve your business needs".
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The life cycle of CRISP-DM includes six phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.
A standardized data mining process is explained in detail that involves a number of phases including business understanding, data understanding, data preparation, modeling, evaluation, and deployment.
The methodology consists of six phases (Fig. 2), starting with the initial phase of understanding the project (Introduction), followed by data understanding (EEG Acquisition/Processing), data pre-processing, data modeling, evaluation and ending up with the deployment (knowledge discovery) [ 45].
The second phase includes analyzing and exploring the available data and understanding what it means (data understanding).
1. Business understanding phase Zan et al. (2007) demonstrated that business understanding can be established via understanding the goals and data mining requirements.
Business understanding phase.
Data understanding 3.
3) Target data understanding - deep understanding of target data scheme up to the level of attributes.
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