基础Pipeline构建

from sklearn.datasets import load_iris
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline
from sklearn.metrics import accuracy_score
iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(____)
pipe = Pipeline([('____', StandardScaler()), ('____', MLPClassifier(hidden_layer_sizes=(____,), max_iter=____, random_state=____))])
pipe.fit(____)
print(____)