text_plain_output_1.png
from sklearn.neural_network import MLPClassifier

from sklearn.preprocessing import StandardScaler

clf = MLPClassifier(random_state=1)
clf.fit(X_train, y_train)
clf.score(X_test, y_test)

clf = MLPClassifier(random_state=1)
clf.fit(X2_train, y2_train)
clf.score(X2_test, y2_test)

scaler = StandardScaler()
scaler.fit(X_train)
X_train = scaler.transform(X_train)
X_test = scaler.transform(X_test)

clf = MLPClassifier(random_state=1)
clf.fit(X_train, y_train)
clf.score(X_test, y_test)

scaler = StandardScaler()
scaler.fit(X2_train)
X2_train = scaler.transform(X2_train)
X2_test = scaler.transform(X2_test)

clf = MLPClassifier(random_state=1)
clf.fit(X2_train, y2_train)
clf.score(X2_test, y2_test)