Probabilities Do Not Match for Scikit Learn's GradientBoostingClassifier about coremltools HOT 2 CLOSED

from sklearn.ensemble import GradientBoostingClassifier
from sklearn.datasets import load_boston
import numpy as np
import pandas as pd

from coremltools.converters import sklearn as skl_converter

args = {'max_leaf_nodes': None, 'min_samples_leaf': 1, 'min_samples_split': 2,
        'min_weight_fraction_leaf': 0.5, 'max_features': 1, 'max_depth': 1}

scikit_model = GradientBoostingClassifier(random_state = 1, **args)

scikit_data = load_boston()
X = scikit_data.data.astype('f').astype('d')

num_classes = 3
t = scikit_data.target
target = np.digitize(t, np.histogram(t, bins = num_classes - 1)[1]) - 1
scikit_model.fit(X, target)

coreml_model = skl_converter.convert(scikit_model, scikit_data.feature_names)

df = pd.DataFrame(X, columns=scikit_data.feature_names)

for i, row in df.iterrows():
    y_cm = coreml_model.predict(dict(row))['classProbability']
    y_sk = scikit_model.predict_proba([X[i]])
    for i in range(3):
        assert(np.isclose(y_cm[i], y_sk[0][i]))