There are several types of model validation, each serving a specific purpose:
1. Internal Validation: This involves testing the model on the same dataset that was used to develop it. Although it can assess the model's performance on known data, it may lead to overfitting. 2. External Validation: This assesses the model's performance on a different dataset than the one used for development. It provides a more robust evaluation of the model's generalizability. 3. Temporal Validation: This type involves testing the model on data from a different time period to ensure its applicability over time. 4. Geographical Validation: This assesses the model's performance in different geographical locations to ensure its adaptability across various settings.
