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[python-package] use f-strings for concatenation in examples/python-guide/logistic_regression.py #4356

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Jun 8, 2021
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[python-package] use f-strings for concatenation in examples/python-guide/logistic_regression.py #4356

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064e486
updated with f-string migration
sagnik1511 Jun 8, 2021
01380fb
Update logistic_regression.py
sagnik1511 Jun 8, 2021
8ce3f0f
Update logistic_regression.py
sagnik1511 Jun 8, 2021
149be7a
Update logistic_regression.py
sagnik1511 Jun 8, 2021
376eff5
Update logistic_regression.py
sagnik1511 Jun 8, 2021
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8 changes: 4 additions & 4 deletions examples/python-guide/logistic_regression.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ def experiment(objective, label_type, data):
"""
np.random.seed(0)
nrounds = 5
lgb_data = data['lgb_with_' + label_type + '_labels']
lgb_data = data[f"lgb_with_{label_type}_labels"]
params = {
'objective': objective,
'feature_fraction': 1,
Expand All @@ -81,7 +81,7 @@ def experiment(objective, label_type, data):
time_zero = time.time()
gbm = lgb.train(params, lgb_data, num_boost_round=nrounds)
y_fitted = gbm.predict(data['X'])
y_true = data[label_type + '_labels']
y_true = data[f"{label_type}_labels"]
duration = time.time() - time_zero
return {
'time': duration,
Expand Down Expand Up @@ -113,5 +113,5 @@ def experiment(objective, label_type, data):
for k in range(K)]
B = [experiment('xentropy', label_type='binary', data=DATA)['time']
for k in range(K)]
print('Best `binary` time: ' + str(min(A)))
print('Best `xentropy` time: ' + str(min(B)))
print(f"Best `binary` time: {min(A)}")
print(f"Best `xentropy` time: {min(B)}")