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from sklearn.model_selection import cross_val_score
from catboost import CatBoostClassifier
from sklearn.datasets import load_breast_cancer
from hyperactive import Hyperactive
data = load_breast_cancer()
X, y = data.data, data.target
def model(opt):
cbc = CatBoostClassifier(
iterations=10, depth=opt["depth"], learning_rate=opt["learning_rate"]
)
scores = cross_val_score(cbc, X, y, cv=3)
return scores.mean()
search_space = {
"depth": list(range(2, 12)),
"learning_rate": [1e-3, 1e-2, 1e-1, 0.5, 1.0],
}
hyper = Hyperactive()
hyper.add_search(model, search_space, n_iter=10)
hyper.run()
SimonBlanke /
Hyperactive
