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.
This exercise is part of the course
Monitoring Machine Learning in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
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()