log loss python
sklearn.metrics.log_loss(y_true, y_pred, *, eps=1e-15, normalize=True, sample_weight=None, labels=None)
log loss python
sklearn.metrics.log_loss(y_true, y_pred, *, eps=1e-15, normalize=True, sample_weight=None, labels=None)
python logistic function
import numpy as np
def logistic(x):
return 1 / (1 + np.exp(-x))
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