from aizoo.tab.models import TabNetClassifier
from sklearn.datasets import make_regression, make_classification
from sklearn.metrics import r2_score, roc_auc_score
X, y = make_classification(n_samples=10000)
TabNetClassifier().run(X, y, feval=roc_auc_score)
from aizoo.tuner.optimizers import LGBOptimizer, F1Optimizer
from sklearn.datasets import make_regression, make_classification
X, y = make_classification(n_samples=1000)
opt = LGBOptimizer('search_space.yaml', X, y)
best_params = opt.optimize(100)
opt.plot()