def RandomTreesEmbeddingAlgo(x_train_vft, y_train, x_test_vft, y_test, vec):
print("Random Trees Embedding")
rte = RandomTreesEmbedding(n_jobs=2, random_state=0)
rte.fit(x_train_vft, y_train)
y_predict_class = rte.predict(x_test_vft)
print("Confusion Matrix")
print(confusion_matrix(np.array(y_test), np.array(y_predict_class)))
print('Accuracy Score :', accuracy_score(y_test, y_predict_class))
print('ROC(Receiver Operating Characteristic) and AUC(Area Under Curve)', roc_auc_score(y_test, y_predict_class))
print('Average Precision Score:', average_precision_score(y_test, y_predict_class))
if rte.predict(vec) == [1]:
return "Positive"
else:
return "Negative"
