Authorizations
Path Parameters
Project ID
Learn Block ID, use the impulse functions to retrieve the ID
Body
Only fields defined in this object are set
Whether to use visual or expert mode.
expert, visual DEPRECATED, use "setImpulseThresholds" instead. Minimum confidence score, if the neural network scores a sample below this threshold it will be flagged as uncertain.
The model type to select, as described in the model metadata call.
int8, float32, akida, requiresRetrain Raw Keras script (only used in expert mode)
The visual layers for the neural network (only in visual mode).
Number of training cycles (only in visual mode).
Learning rate (between 0 and 1) (only in visual mode).
Batch size used during training (only in visual mode).
Train/test split (between 0 and 1)
Whether to automatically balance class weights, use this for skewed datasets.
Use learned optimizer and ignore learning rate.
The data augmentation policy to use with image input
none, all Whether to profile the i8 model (might take a very long time)
If set, skips creating embeddings and measuring memory (used in tests)
If the 'custom validation split' experiment is enabled, this metadata key is used to prevent group data leakage between train and validation datasets.
Whether the 'Advanced training settings' UI element should be expanded.
Whether the 'Augmentation training settings' UI element should be expanded.
Training parameters, this list depends on the list of parameters that the model exposes.
Capacity level for visual anomaly detection. Determines which set of default configurations to use. The higher capacity, the higher number of (Gaussian) components, and the more adapted the model becomes to the original distribution
low, medium, high Last shown variant on the Keras screen. Used to keep the same view after refreshing.
int8, float32, akida Training parameters specific to the type of the learn block. Parameters may be adjusted depending on the model defined in the visual layers. Used for our built-in blocks.