Show pageOld revisionsBacklinksBack to top This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong. # Validation and overfitting ## Conclusion 1. Validation helps us evaluate a quality of the model 2. Validation helps us select the model which will perform best on the unseen data 3. Underfitting refers to not capturing enough patterns in the data low model's quality on test data, which was unexpected due to validation scores ## 출처 - https://www.coursera.org/learn/competitive-data-science/lecture/wwGFq/validation-and-overfitting open/validation-and-overfitting.txt Last modified: 2024/10/05 06:15by 127.0.0.1