Reconstruction accuracy measures how well the model can recreate the input data.
- High reconstruction accuracy means the model has learned the normal patterns of the data well.
- Low reconstruction accuracy means the model may not have learned the data properly, or the data may contain too much noise or anomalies.
The closer the reconstruction accuracy is to 1 (the maximum score), the higher the anomaly detection accuracy.