Meet error when load xgboost model which trained with the API in sklearn

[frontword]

leaves does not support the sklearn xgboost model ?
I use the below python code to train one xgboost model, meet error when use the below API to load this model in go code
leaves.XGEnsembleFromFile("xg_iris.model", false)

---

The error :
mark@mark:~/golang $ go run predict_iris.go
Name: xgboost.gbtree
NFeatures: 4
NOutputGroups: 3
NEstimators: 100
panic: different sizes: len(a) = 30, len(b) = 90

goroutine 1 [running]:
main.main()
/home/mark/golang/predict_iris.go:44 +0x686
exit status 2

---

Below is the python code to train the xgboost model using the xgboost API in sklearn:
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
import xgboost as xgb
from xgboost.sklearn import XGBClassifier

X, y = datasets.load_iris(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

xg_train = xgb.DMatrix(X_train, label=y_train)
xg_test = xgb.DMatrix(X_test, label=y_test)
params = {
'objective': 'multi:softmax',
'num_class': 3,
}
n_estimators = 5
#clf = xgb.train(params, xg_train, n_estimators)
clf = XGBClassifier(**params)
clf = clf.fit(X_train, y_train)
y_pred = clf.predict_proba(X_test)[:,1]
clf.save_model('xg_iris.model')
np.savetxt('xg_iris_true_predictions.txt', y_pred, delimiter='\t')
datasets.dump_svmlight_file(X_test, y_test, 'iris_test.libsvm')

[dmitryikh]

@frontword , thank you for your detailed feedback.

leaves does not support the sklearn xgboost model ?

Currently, models generated from xgboost sklearn API are not tested. I thought, that xgboost sklearn API produces the same models as xgboost python API.

I will check you case and will come back yo you soon.