<jupyter_start><jupyter_text>Test of AutoML on London Crime Data vs. LightGBM GridSearched<jupyter_code>import pandas as pd
import auto_ml
from lightgbm import LGBMRegressor
# LOAD DATA
crime = pd.read_csv('../data/raw/crime/MPS_Ward_Level_Crime_Historic_OldWardtoMar2010.csv')
# OVERVIEW OF DATA
crime.head()
# DROP UNNECESSARY FEATURES
crime = crime.drop('Ward Code', axis=1)
# CREATE A TARGET VARIABLE - LAST MONTH - SEE IF WE CAN PREDICT BASED ON DATA FROM THE PREVIOUS 10 YEARS
crime['201003'].describe()
# CREATE A BASE REGRESSOR
lgb =<jupyter_output><empty_output>
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