CRISP-DM
CRISP-DM (Cross-Industry Standard Process for Data Mining) is a widely used and comprehensive data mining process model that provides a structured approach to planning, building, deploying, and maintaining data mining solutions. It consists of six phases: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The Business Understanding phase involves understanding the project objectives and requirements, while the Data Understanding phase involves collecting and exploring the data. The Data Preparation phase involves cleaning, transforming, and integrating the data, while the Modeling phase involves selecting and applying appropriate modeling techniques. The Evaluation phase involves assessing the quality and effectiveness of the models, and the Deployment phase involves deploying the models into the operational environment. CRISP-DM provides a flexible and iterative approach to data mining that can be adapted to different types of projects and data. It is widely used in both academic and industry settings.
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