Hide RandomizedSearchCV output - scikit-learn

Question

I'm executing pylint in the terminal to clean up my python script a bit. In my script, I also use RandomizedSearchCV. What can I do so that pylint's results do not show the different combinations of the RandomizedSearchCV results? Or how can I suppress the output from RandomizedSearchCV?
Here's a snippet of the code in my .py script that causes this issue, and the screenshots of the start/end of what I see when I execute in the terminal.
LOGGER.info("Fine tune model and fit it (Model 2)")
# with warnings.catch_warnings():
# warnings.filterwarnings("ignore")
new_model = RandomizedSearchCV(lr_alt, parameters, cv=4, n_iter=15)
# with warnings.catch_warnings():
# warnings.filterwarnings("ignore")
new_model.fit(train_features_x, train_y)
Can't load images yet, but here's a snippet of the start code in terminal:
(env-stats404-w20-HW5) Franciscos-MacBook-Pro:FRANCISCO-AVALOS franciscoavalosjr$ pylint main.py
************* Module main
main.py:69:0: C0103: Argument name "Product" doesn't conform to snake_case naming style (invalid-name)
main.py:80:4: R1705: Unnecessary "elif" after "return" (no-else-return)
main.py:89:75: W0108: Lambda may not be necessary (unnecessary-lambda)
Traceback (most recent call last):
File "/Users/franciscoavalosjr/opt/anaconda3/envs/env-stats404-w20-HW5/bin/pylint", line 8, in <module>
sys.exit(run_pylint())
File "/Users/franciscoavalosjr/opt/anaconda3/envs/env-stats404-w20-HW5/lib/python3.7/site-packages/pylint/__init__.py", line 23, in run_pylint
PylintRun(sys.argv[1:])
And here's a snippet of the end of that pylint run:
File "/Users/franciscoavalosjr/opt/anaconda3/envs/env-stats404-w20-HW5/lib/python3.7/site-packages/astroid/decorators.py", line 131, in raise_if_nothing_inferred
yield next(generator)
File "/Users/franciscoavalosjr/opt/anaconda3/envs/env-stats404-w20-HW5/lib/python3.7/site-packages/astroid/decorators.py", line 88, in wrapped
if context.push(node):
File "/Users/franciscoavalosjr/opt/anaconda3/envs/env-stats404-w20-HW5/lib/python3.7/site-packages/astroid/context.py", line 92, in push
self.path.add((node, name))
RecursionError: maximum recursion depth exceeded while calling a Python object
(env-stats404-w20-HW5) Franciscos-MacBook-Pro:FRANCISCO-AVALOS franciscoavalosjr$

Answer 1

Turns out python didn't like how I assigned my new column. The fix came from creating a new variable with the new formed column instead of adding it to my dataframe. Before and after code below:
Original code:
# DF_MAJORITY = SUB_DATA[SUB_DATA['balance'] == 0]
# DF_MINORITY = SUB_DATA[SUB_DATA['balance'] == 1]
# NEW_MAJORITY_NUMBER = ((DF_MINORITY.shape[0]/0.075) - DF_MINORITY.shape[0])
# NEW_MAJORITY_NUMBER = int(round(NEW_MAJORITY_NUMBER))
# DF_MAJORITY_DOWNSAMPLED = resample(DF_MAJORITY, replace=False, n_samples=NEW_MAJORITY_NUMBER,
# random_state=29)
# DF_DOWNSAMPLED = pd.concat([DF_MAJORITY_DOWNSAMPLED, DF_MINORITY])
New Code:
BALANCE = SUB_DATA.loc[:, 'Delivery Status'].apply(lambda x: classify_shipping(x))
BALANCE = pd.DataFrame(BALANCE)
DF_MAJORITY = BALANCE[BALANCE['Delivery Status'] == 0]
DF_MINORITY = BALANCE[BALANCE['Delivery Status'] == 1]
NEW_MAJORITY_NUMBER = ((DF_MINORITY.shape[0]/0.075) - DF_MINORITY.shape[0])
NEW_MAJORITY_NUMBER = int(round(NEW_MAJORITY_NUMBER))
DF_MAJORITY_DOWNSAMPLED = resample(DF_MAJORITY, replace=False,
n_samples=NEW_MAJORITY_NUMBER, random_state=29)
DF_DOWNSAMPLED = pd.concat([DF_MAJORITY_DOWNSAMPLED, DF_MINORITY])