Core Evaluation Metrics
Classification Metrics
Accuracy, Precision, Recall, F1-Score, ROC-AUC for image classification tasks
Detection Metrics
mAP, IoU, Precision-Recall curves for object detection evaluation
Segmentation Metrics
Pixel accuracy, IoU, Dice coefficient, Hausdorff distance for segmentation
Evaluation Approaches
Cross-Validation
K-fold, stratified, and time series CV for robust model assessment
Hold-out Validation
Train/validation/test splits with proper data distribution
Bootstrap Sampling
Statistical confidence intervals and uncertainty estimation