Final answer:
The CRISP-DM life cycle consists of six phases: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. These phases help structure the process of data mining and require iterative refinement throughout the project.
Step-by-step explanation:
The CRISP-DM (Cross-Industry Standard Process for Data Mining) life cycle includes six phases that guide the process of data mining in a structured manner. Although the information provided refers to a different model, the six phases of the CRISP-DM life cycle are: Business Understanding - This initial phase focuses on understanding the project objectives and requirements from a business perspective.
Data Understanding - Involves collecting initial data and proceeding with activities to get familiar with the data, identify data quality problems, and discover first insights. Data Preparation - In this phase, data is prepared for modeling by selecting cases, cleaning data, and constructing data that will be used in the modeling process. Modeling - Various modeling techniques are applied, and their parameters are calibrated to optimal values.
Evaluation - The models are thoroughly evaluated, and the steps are reviewed to ensure that the model effectively achieves the business objectives. Deployment - The final phase involves deploying the model into the operation environment or, depending on the requirements, implementing the model's insights into decision-making processes. The CRISP-DM life cycle is iterative, often requiring one to go back to previous steps and refine them before moving forward.