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)

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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

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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.