INNER CODE UNIT · Python
estimate_score
alteryx/open_source_demos · predict-correct-answer/utils.py:116
def estimate_score(fm_enc, label, splitter):
k = 0
for train_index, test_index in splitter.split(fm_enc):
clf = RandomForestClassifier()
X_train, X_test = fm_enc.iloc[train_index], fm_enc.iloc[test_index]
y_train, y_test = label[train_index], label[test_index]
clf.fit(X_train, y_train)
preds = clf.predict(X_test)
score = round(roc_auc_score(preds, y_test), 2)
print("AUC score on time split {} is {}".format(k, score))
def feature_importances(fm_enc, clf, feats=5):
feature_imps = [(imp, fm_enc.columns[i])
for i, imp in enumerate(clf.feature_importances_)]
feature_imps.sort()
feature_imps.reverse()
print('Feature Importances: ')