Persistent Model#
The Persistent Model meta-estimator wraps a Persistable learner with additional functionality for saving and loading the model. It uses Persister objects to interface with various storage backends such as the Filesystem.
Interfaces: Estimator, Learner, Probabilistic, Scoring
Data Type Compatibility: Depends on base learner
Parameters#
# | Name | Default | Type | Description |
---|---|---|---|---|
1 | base | Persistable | The persistable base learner. | |
2 | persister | Persister | The persister used to interface with the storage system. | |
3 | serializer | RBX | Serializer | The object serializer. |
Examples#
use Rubix\ML\PersistentModel;
use Rubix\ML\Clusterers\KMeans;
use Rubix\ML\Persisters\Filesystem;
use Rubix\ML\Serializers\RBX;
$estimator = new PersistentModel(new KMeans(10), new Filesystem('example.model'), new RBX());
Additional Methods#
Load the model from storage:
public static load(Persister $persister, ?Serializer $serializer = null) : self
use Rubix\ML\PersistentModel;
use Rubix\ML\Persisters\Filesystem;
use Rubix\ML\Serializers\RBX;
$estimator = PersistentModel::load(new Filesystem('example.model'), new RBX());
Save the model to storage:
public save() : void
$estimator->save();
Last update:
2021-04-01