"""Module for LightGBM classification."""
from jarvis.ai.pkgs.sklearn.classification import classification as sk_cl
[docs]def classification(
X=[],
Y=[],
tol=100,
plot=False,
preprocess=False,
models=[],
model_name="my_model",
save_model=False,
):
"""Provide function for classification models."""
info = sk_cl(
X=X,
Y=Y,
tol=tol,
preprocess=preprocess,
models=models,
model_name=model_name,
save_model=save_model,
)
return info
"""
if __name__ == "__main__":
from jarvis.ai.pkgs.utils import get_ml_data, binary_class_dat
property = "exfoliation_energy"
tol=100
#property = 'optb88vdw_bandgap'
#tol=0.05
X, Y, jid = get_ml_data(dataset="cfid_3d", ml_property=property)
#X_class, Y_class = binary_class_dat(X=X, Y=Y, tol=tol)
print ('lennnn',len(X))
#models = [LGBMClassifier(n_estimators=1000,max_depth=50,num_leaves=100)]
models = [LGBMClassifier()]
info = classification(X=X, Y=Y, models=models,
preprocess=False, save_model=False, tol=tol)
print (info['LGBMClassifier']['roc_auc'][0])
"""