Get metadata about a trained anomaly block. Use the impulse blocks to find the learnId.
Project ID
Learn Block ID, use the impulse functions to retrieve the ID
OK
Whether the operation succeeded
Optional error description (set if 'success' was false)
Date when the model was trained
Scale input for StandardScaler. Values are scaled like this (where ix is axis index): input[ix] = (input[ix] - mean[ix]) / scale[ix];
Mean input for StandardScaler. Values are scaled like this (where ix is axis index): input[ix] = (input[ix] - mean[ix]) / scale[ix];
Trained K-means clusters
Center of each cluster (one value per axis)
Size of the cluster
Which axes were included during training (by index)
"`[ 0, 11, 22 ]`"Default minimum confidence rating required before tagging as anomaly, based on scores of training data (GMM only).
The types of model that are available
Metrics for each of the available model types
The model's loss on the validation set after training
The model's accuracy on the validation set after training
Precision, recall, F1 and support scores
Custom, device-specific performance metrics
The name of the metric
The value of this metric for this model type
Only set for object detection projects
Only set for visual anomaly projects. 2D array of shape (n, n) with raw anomaly scores, where n varies based on the image input size and the specific visual anomaly algorithm used. The scores corresponds to each grid cell in the image's spatial matrix.
If this is set, then we're still profiling this model. Subscribe to job updates to see when it's done (afterward the metadata will be updated).
If this is set, then the profiling job failed (get the status by getting the job logs for 'profilingJobId').