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NEW QUESTION: 1
You have a dataset that contains 2,000 rows. You are building a machine learning classification model by using Azure Learning Studio. You add a Partition and Sample module to the experiment.
You need to configure the module. You must meet the following requirements:
* Divide the data into subsets
* Assign the rows into folds using a round-robin method
* Allow rows in the dataset to be reused
How should you configure the module? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Use the Split data into partitions option when you want to divide the dataset into subsets of the data. This option is also useful when you want to create a custom number of folds for cross-validation, or to split rows into several groups.
Add the Partition and Sample module to your experiment in Studio (classic), and connect the dataset.
For Partition or sample mode, select Assign to Folds.
Use replacement in the partitioning: Select this option if you want the sampled row to be put back into the pool of rows for potential reuse. As a result, the same row might be assigned to several folds.
If you do not use replacement (the default option), the sampled row is not put back into the pool of rows for potential reuse. As a result, each row can be assigned to only one fold.
Randomized split: Select this option if you want rows to be randomly assigned to folds.
If you do not select this option, rows are assigned to folds using the round-robin method.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample

NEW QUESTION: 2
Which Symantec product is best suited for simultaneously administering a large number of ProxySG appliances? (Choose the best answer.)
A. PacketShaper
B. Content Analysis
C. Management Center
D. Reporter
Answer: C

NEW QUESTION: 3
Which of the following auditing techniques would be used to detect the validity of a credit card transaction based on time, location, and date of purchase?
A. Benford's analysis
B. Stratified sampling
C. Gap analysis
D. Data mining
Answer: B