rfecv.py

from sklearn.metrics import f1_score, make_scorer
from sklearn.feature_selection import RFECV
from sklearn.ensemble import RandomForestClassifier

# Custom scorer for cross validation
scorer = make_scorer(f1_score, greater_is_better=True, average = 'macro')

# Create a model for feature selection
estimator = RandomForestClassifier(n_estimators = 100,  n_jobs = -1)

# Create the object
selector = RFECV(estimator, step = 1, cv = 3, 
                 scoring= scorer, n_jobs = -1)

# Fit on training data
selector.fit(train, train_labels)

# Transform data
train_selected = selector.transform(train)
test_selected = selector.transform(test)