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 or Redis.
Interfaces: Wrapper, 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 medium. |
Examples#
use Rubix\ML\PersistentModel;
use Rubix\ML\Clusterers\KMeans;
use Rubix\ML\Persisters\Filesystem;
$estimator = new PersistentModel(new KMeans(10), new Filesystem('example.model'));
Additional Methods#
Load the model:
public static load(Persister $persister) : self
use Rubix\ML\PersistentModel;
use Rubix\ML\Persisters\Filesystem;
$estimator = PersistentModel::load(new Filesystem('example.model'));
Save the model:
public save() : void
$estimator->save();
Last update: 2021-01-23