import pandas as pd
# scikit learn utilites
from sklearn.datasets import load_digits
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
# mljar-supervised package
from supervised.automl import AutoML

# load the data
digits = load_digits()
X_train, X_test, y_train, y_test = train_test_split(
    pd.DataFrame(digits.data), digits.target, stratify=digits.target, test_size=0.25,
    random_state=123
)

# train models with AutoML
automl = AutoML(mode="Perform")
automl.fit(X_train, y_train)

# compute the accuracy on test data
predictions = automl.predict_all(X_test)
print(predictions.head())
print("Test accuracy:", accuracy_score(y_test, predictions["label"].astype(int)))