binary classification scorers

scorers.py

import numpy as np
import pandas as pd
from scipy.stats import ks_2samp
from sklearn.metrics import make_scorer, roc_auc_score, log_loss
from sklearn.model_selection import GridSearchCV

def ks_stat(y, yhat):
    return ks_2samp(yhat[y==1], yhat[y!=1]).statistic


ks_scorer = make_scorer(ks_stat, needs_proba=True)

log_scorer = make_scorer(roc_auc_score, needs_proba=True, greater_is_better=False)

roc_scorer = make_scorer(log_loss, needs_proba=True)


grid = GridSearchCV(pl, param_grid=param_grid, scoring={'auc': roc_scorer, 'log': log_scorer}
    , refit='log')