CRISP-DM's full form is CRoss-InduStry Process for Data Mining. CRISP-DM is a well-defined, well-structured, and well-proven process for machine learning, data mining, and business intelligence projects. It is a robust, flexible, cyclic, useful, and practical approach to solving business problems. The process discovers hidden valuable information or patterns from several databases. The CRISP-DM process has six major phases:
- Business Understanding: In this first phase, the main objective is to understand the business scenario and requirements for designing an analytical goal and initial action plan.
- Data Understanding: In this phase, the main objective is to understand the data and its collection process, perform data quality checks, and gain initial insights.
- Data Preparation: In this phase, the main objective is to prepare analytics-ready data. This involves handling missing values, outlier detection and handling, normalizing data, and feature engineering. This phase...
