About this document
Model Quality Validation Techniques by hwefhwfb is a document available to read on EtoBox.
The document outlines two primary methods for validating model quality: Train-Test Split Evaluation and Cross Validation. Train-Test Split involves dividing a dataset into training and test subsets to evaluate model performance, while Cross Validation uses multiple subsets to provide a more accurate measure of model quality, especially useful for smaller datasets. It also discusses performance metrics like Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) for assessing prediction accuracy.
- Author
- hwefhwfb
- Language
- EN