DashAI.back.optimizers.OptunaOptimizer

class OptunaOptimizer(n_trials=None, sampler=None, pruner=None)[source]

Methods

`__init__`([n_trials, sampler, pruner])
`contour_plot`(trials)	Contour plot between two hyperparameters and the goal metric achieved in the search space.
`create_plots`(trials, run_id, n_params)	List of available plots.
`get_model`()	Get the model with the best set of hyperparameters found
`get_schema`()	Generates the component related Json Schema.
`get_trials_values`()	Get the trial values from the hyperparameter optimization process
`history_objective_plot`(trials)	Plot for the goal metric achieved per trial.
`importance_plot`(trials)	Plot to obtain the importance between all the hyperparameters involved in hyperparameter optimization.
`optimize`(model, input_dataset, ...)	Optimization process
`slice_plot`(trials)	Plot that compares the performance in the search space of one hyperparameter.
`validate_and_transform`(raw_data)	It takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.

Attributes