Learn how to effectively evaluate the precision and recall of AI models, especially when working with small question datasets. This guide covers the concepts, calculation methods, and practical considerations using scikit-learn.
ai / precision / recall / evaluation / small dataset / machine learning / scikit-learn / classification
Understand the differences between Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), how to choose the right metric for your prediction task, and the impact of large errors on each.
regression / model evaluation / MAE / RMSE / error metrics / scikit-learn / machine learning
Read training and validation scores together, fit preprocessing inside a pipeline and keep a final test set out of model selection.
Machine Learning / Validation / Overfitting