import numpy as np
from rslearn.linear_model import LinearRegression

# Training data
X = np.array([
    [1],
    [2],
    [3],
    [4],
    [5],
])

y = np.array([2, 4, 6, 8, 10])

# Train the model
model = LinearRegression()
model.fit(X, y, scale=True) # Auto Scales Data, saves time

# Make predictions
predictions = model.predict(np.array([[6], [7]])) # Scales new data also on saved StandardScaler configs.
print(predictions)

# Evaluations
evals = model.evaluate_model(y_pred=predictions, y_true=[12, 14])
print(evals) 
# This will return r2_score, rmse, mse, mae at once