Which technique should you use?

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.

View Answer

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

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data