def test_hyperopt(self):
job = Job.objects.create(
split=create_test_split(split_type=SplitTypes.SPLIT_SINGLE.value,
original_log=create_test_log(
log_name=general_example_filename,
log_path=general_example_filepath)),
encoding=create_test_encoding(
value_encoding=ValueEncodings.SIMPLE_INDEX.value,
prefix_length=3,
padding=False),
labelling=create_test_labelling(
label_type=LabelTypes.REMAINING_TIME.value),
clustering=create_test_clustering(
clustering_type=ClusteringMethods.KMEANS.value),
predictive_model=create_test_predictive_model(
predictive_model=PredictiveModels.CLASSIFICATION.value,
prediction_method=ClassificationMethods.RANDOM_FOREST.value),
hyperparameter_optimizer=create_test_hyperparameter_optimizer(
hyperoptim_type=HyperparameterOptimizationMethods.HYPEROPT.
value,
performance_metric=HyperOptLosses.ACC.value,
max_evals=2))
prediction_task(job.pk)
job = Job.objects.get(pk=1)
self.assertFalse(classification_random_forest(
) == job.predictive_model.classification.__getattribute__(
ClassificationMethods.RANDOM_FOREST.value.lower()).to_dict())
def get_classification_job(predictive_model: str, prediction_method: str, metric: HyperOptLosses = HyperOptLosses.ACC.value):
encoding = create_test_encoding(prefix_length=8, padding=True)
pred_model = create_test_predictive_model(predictive_model=predictive_model,
prediction_method=prediction_method)
hyperparameter_optimizer = create_test_hyperparameter_optimizer(performance_metric=metric)
job = create_test_job(predictive_model=pred_model,
encoding=encoding,
hyperparameter_optimizer=hyperparameter_optimizer)
return job
def get_regression_job(predictive_model: str, prediction_method: str,
metric: HyperOptLosses = HyperOptLosses.ACC.value):
encoding = create_test_encoding(prefix_length=8, padding=True)
pred_model = create_test_predictive_model(predictive_model=predictive_model,
prediction_method=prediction_method)
hyperparameter_optimizer = create_test_hyperparameter_optimizer(performance_metric=metric)
job = create_test_job(predictive_model=pred_model,
encoding=encoding,
labelling=create_test_labelling(label_type=LabelTypes.REMAINING_TIME.value,
threshold_type=ThresholdTypes.NONE.value),
hyperparameter_optimizer=hyperparameter_optimizer)
return job