accuracy precision recall

from sklearn.neural_network import MLPClassifier
from sklearn.metrics import precision_score,recall_score

# Create a classifier: a support vector classifier
mlp = MLPClassifier()

# Split data into 50% train and 50% test subsets
X_train, X_test, y_train, y_test = train_test_split(digits.data, digits.target, test_size=0.5, shuffle=False)

# Learn the digits on the train subset
mlp.fit(X_train, y_train)

# Predict the value of the digit on the test subset
predicted = mlp.predict(X_test)

print("Precision Score:",precision_score(y_test, predicted,average='micro'))
print("Recall Score:",recall_score(y_test, predicted,average='micro'))