You use Azure Machine Learning to train a model based on a dataset named dataset1. You define a dataset monitor and create a dataset named dataset2 that contains new data. You need to compare dataset1

The correct answer is C. backfill. The backfill method of the DataDriftDetector class is used to run a dataset monitor against historical data - specifically to compare a baseline dataset (dataset1) against a target dataset (dataset2) over a defined time range. This is the mechanism to trigger drift analysis betwe

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Question

You use Azure Machine Learning to train a model based on a dataset named dataset1. You define a dataset monitor and create a dataset named dataset2 that contains new data. You need to compare dataset1 and dataset2 by using the Azure Machine Learning SDK for Python. Which method of the DataDriftDetector class should you use?

Options

Arun
Bget
Cbackfill
Dupdate

How the community answered

(32 responses)

A
6% (2)
B
6% (2)
C
75% (24)
D
13% (4)

Explanation

The backfill method of the DataDriftDetector class is used to run a dataset monitor against historical data - specifically to compare a baseline dataset (dataset1) against a target dataset (dataset2) over a defined time range. This is the mechanism to trigger drift analysis between an existing baseline and newly collected data. The run method schedules future monitoring runs, get retrieves an existing detector by name, and update modifies detector settings - none of these compare two datasets directly.

Topics

#Azure Machine Learning SDK#Data Drift#Dataset Monitoring#DataDriftDetector

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