bias variance tradeoff

from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error
from sklearn.model_selection import cross_val_score, train_test_split


# Train a linear regression model
lr = LinearRegression()
lr.fit(X_train, y_train)

# Evaluate the model using cross-validation
cv_scores = cross_val_score(lr, X_train, y_train, cv=5, scoring='neg_mean_squared_error')
cv_scores = -cv_scores

# Calculate the average MSE and its standard deviation
avg_mse = cv_scores.mean()
std_mse = cv_scores.std()

print(f"Cross-Validation MSE: {avg_mse:.2f} +/- {std_mse:.2f}")