from sklearn.datasets import load_diabetes
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error, r2_score
from sklearn.model_selection import train_test_split

X, y = load_diabetes(return_X_y=True)

X_train, X_test, y_train, y_test = train_test_split(
    X,
    y,
    test_size=0.2,
    random_state=42,
)

model = LinearRegression()
model.fit(X_train, y_train)

predictions = model.predict(X_test)

print(f"train rows: {X_train.shape[0]}")
print(f"test rows: {X_test.shape[0]}")
print(f"intercept: {model.intercept_:.2f}")
print(f"coefficients: {model.coef_.round(2).tolist()}")
print(f"first predictions: {predictions[:3].round(1).tolist()}")
print(f"mean absolute error: {mean_absolute_error(y_test, predictions):.2f}")
print(f"r2 score: {r2_score(y_test, predictions):.3f}")