Recipe: How to plot a learning Curve in Python?

How to plot a learning Curve in Python?

This recipe helps you plot a learning Curve in Python
In [2]:
## How to plot a learning Curve in Python
def Snippet_139():
    print(format('How to plot a learning Curve in Python','*^82'))

    import warnings

    # load libraries
    import numpy as np
    import matplotlib.pyplot as plt
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.datasets import load_digits
    from sklearn.model_selection import learning_curve

    # Load data
    digits = load_digits()

    # Create feature matrix and target vector
    X, y =,

    # Plot Learning Curve
    # Create CV training and test scores for various training set sizes
    train_sizes, train_scores, test_scores = learning_curve(RandomForestClassifier(),
                                               X, y, cv=10, scoring='accuracy', n_jobs=-1,
                                               # 50 different sizes of the training set
                                               train_sizes=np.linspace(0.01, 1.0, 50))

    # Create means and standard deviations of training set scores
    train_mean = np.mean(train_scores, axis=1)
    train_std = np.std(train_scores, axis=1)

    # Create means and standard deviations of test set scores
    test_mean = np.mean(test_scores, axis=1)
    test_std = np.std(test_scores, axis=1)

    # Draw lines
    plt.subplots(1, figsize=(10,10))
    plt.plot(train_sizes, train_mean, '--', color="#111111",  label="Training score")
    plt.plot(train_sizes, test_mean, color="#111111", label="Cross-validation score")

    # Draw bands
    plt.fill_between(train_sizes, train_mean - train_std, train_mean + train_std, color="#DDDDDD")
    plt.fill_between(train_sizes, test_mean - test_std, test_mean + test_std, color="#DDDDDD")

    # Create plot
    plt.title("Learning Curve")
    plt.xlabel("Training Set Size"), plt.ylabel("Accuracy Score"), plt.legend(loc="best")

**********************How to plot a learning Curve in Python**********************
In [ ]:

Stuck at work?
Can't find the recipe you are looking for. Let us know and we will find an expert to create the recipe for you. Click here
Companies using this Recipe
1 developer from Deep Learn Labs
1 developer from Rabbit and Tortoise
1 developer from Amazon
1 developer from HCL
1 developer from Vodafone
1 developer from ANAC
1 developer from HvH
1 developer from BAYCC
1 developer from ICFAI