for testing and deploying your application
for finding and fixing issues
for empowering human code reviews
# Author: Simon Blanke
# Email: [email protected]
# License: MIT License
from sklearn.model_selection import cross_validate
from sklearn.utils.validation import _num_samples
class ObjectiveFunctionAdapter:
def __init__(self, estimator) -> None:
self.estimator = estimator
def add_dataset(self, X, y):
self.X = X
self.y = y
def add_validation(self, scoring, cv):
self.scoring = scoring
self.cv = cv
def objective_function(self, params):
cv_results = cross_validate(
self.estimator,
self.X,
self.y,
cv=self.cv,
)
add_info_d = {
"score_time": cv_results["score_time"],
"fit_time": cv_results["fit_time"],
"n_test_samples": _num_samples(self.X),
}
return cv_results["test_score"].mean(), add_info_d
SimonBlanke /
Hyperactive
