from sklearn import datasets
import coremltools
iris = datasets.load_iris()
X = iris.data
y = iris.target
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.5)
from sklearn.ensemble import RandomForestClassifier
my_classifier = RandomForestClassifier()
my_classifier.fit(X_train, y_train)
# Convert model to Core ML
coreml_model = coremltools.converters.sklearn.convert(my_classifier, input_features=iris.feature_names)
