labels_6.py

# Get features at event dates
X = data.loc[labels.index, :]
y = labels['bin']

# Split data
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, shuffle=False)

# Setting random forest parameters
n_estimator = 1000
depth = 2
RANDOM_STATE = 0

rf = RandomForestClassifier(max_depth=depth, n_estimators=n_estimator,
                            criterion='entropy', class_weight='balanced_subsample',
                            random_state=RANDOM_STATE)

# Fitting our model
rf.fit(X_train, y_train)