# save as object
import pickle
s = pickle.dumps(clf)
clf2 = pickle.loads(s)
# save to file
from joblib import dump
dump(clf, 'filename.joblib')
# load from file
from joblib import load
clf = load('filename.joblib')
import pickle
# Save the trained model as a pickle string.
saved_model = pickle.dumps(knn)
# Load the pickled model
knn_from_pickle = pickle.loads(saved_model)
# Use the loaded pickled model to make predictions
knn_from_pickle.predict(X_test)
