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ridge regression alpha values with cross validation score plot

josh.ipynb answered on June 6, 2022 Popularity 1/10 Helpfulness 1/10

answer ridge regression alpha values with cross validation score plot

ridge regression alpha values with cross validation score plot

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# Import necessary modules
from sklearn.linear_model import Ridge
from sklearn.model_selection import cross_val_score

# Setup the array of alphas and lists to store scores
alpha_space = np.logspace(-4, 0, 50)
ridge_scores = []
ridge_scores_std = []

# Create a ridge regressor: ridge
…    
    # Append the mean of ridge_cv_scores to ridge_scores
    ridge_scores.append(np.mean(ridge_cv_scores))
    
    # Append the std of ridge_cv_scores to ridge_scores_std
    ridge_scores_std.append(np.std(ridge_cv_scores))
def display_plot(cv_scores, cv_scores_std):
    fig = plt.figure()
    ax = fig.add_subplot(1,1,1)
    ax.plot(alpha_space, cv_scores)

    std_error = cv_scores_std / np.sqrt(10)

    ax.fill_between(alpha_space, cv_scores + std_error, cv_scores - std_error, alpha=0.2)
    ax.set_ylabel('CV Score +/- Std Error')
    ax.set_xlabel('Alpha')
    ax.axhline(np.max(cv_scores), linestyle='--', color='.5')
    ax.set_xlim([alpha_space[0], alpha_space[-1]])
    ax.set_xscale('log')
    plt.show()
# Display the plot
display_plot(ridge_scores, ridge_scores_std)

Popularity 1/10 Helpfulness 1/10 Language python

Source: campus.datacamp.com

Tags: alpha cross-validation python regression

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Contributed on Jun 06 2022

josh.ipynb

0 Answers Avg Quality 2/10

ridge regression alpha values with cross validation score plot

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