DP-100 Exam Dumps | You need to implement a model development strategy to determine a user's tendency to respond to an ad.

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Question 33/178

You need to implement a model development strategy to determine a user's tendency to respond to an ad.
Which technique should you use?

A. Use a Relative Expression Split module to partition the data based on centroid distance.

B. Use a Relative Expression Split module to partition the data based on distance travelled to the event.

C. Use a Split Rows module to partition the data based on distance travelled to the event.

D. Use a Split Rows module to partition the data based on centroid distance.

Correct Answer: A

Explanation
Split Data partitions the rows of a dataset into two distinct sets.
The Relative Expression Split option in the Split Data module of Azure Machine Learning Studio is helpful when you need to divide a dataset into training and testing datasets using a numerical expression.
Relative Expression Split: Use this option whenever you want to apply a condition to a number column. The number could be a date/time field, a column containing age or dollar amounts, or even a percentage. For example, you might want to divide your data set depending on the cost of the items, group people by age ranges, or separate data by a calendar date.
Scenario:
Local market segmentation models will be applied before determining a user's propensity to respond to an advertisement.
The distribution of features across training and production data are not consistent References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data

Recent Comments (The most recent comments are at the top.)

efor - Oct 24, 2024

The correct answer is D. Use a Split Rows module to partition the data based on centroid distance.

The Split Rows module in Azure Machine Learning can be used to partition data based on specific criteria, such as the centroid distance. This technique is useful for tasks like clustering, where you want to segment the data based on distance to a central point (centroid), which could be relevant in determining a user's tendency to respond to an ad.

The other options are incorrect:

A and B: The Relative Expression Split module is used to split data based on conditional expressions, not on centroid distance or distance traveled.
C: While the Split Rows module is correct, partitioning based on "distance traveled to the event" isn't typically how you assess user tendency for ad response. The centroid distance is more applicable to clustering or proximity-based partitioning.

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