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.
Questo esercizio fa parte del corso
Monitoring Machine Learning in Python
esercizio interattivo pratico
Prova questo esercizio completando questo codice di esempio.
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()