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Different chunking methods

A chunk represents a single data point in the monitoring results. Recall that there are three methods for chunking your data: based on time, size, or the number of chunks.

In this exercise, you will chunk and visualize the results of the CBPE algorithm for the US Census dataset using size-based and number-based chunking methods.

The nannyml library is already imported.

Este exercício faz parte do curso

Monitoring Machine Learning in Python

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Exercício interativo prático

Experimente este exercício completando este código de exemplo.

reference, analysis, analysis_gt = ____.____()

# Initialize the CBPE algorithm
cbpe = nannyml.CBPE(
    y_pred_proba='predicted_probability',
    y_pred='prediction',
    y_true='employed',
    metrics = ['roc_auc', 'accuracy'],
    problem_type = 'classification_binary',
    ____ = ____,
)

cbpe = cbpe.fit(reference)
estimated_results = cbpe.estimate(analysis)
estimated_results.plot().show()
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