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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 dat a. 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
When setting up a data map, which two options are available for handling unmapped dimensions? (Choose two.)
A. Selecting a single unmapped dimension member on the source to map to multiple unmapped dimension members on the target
B. Selecting multiple unmapped dimension members on the source to map to a single unmapped dimension member on the target
C. Selecting a single unmapped dimension member on the source to map to a single unmapped dimension member on the target
D. Selecting multiple unmapped dimension members on the source to map to multiple unmapped dimension members on the target
Answer: B,C
Explanation:
Reference:
https://docs.oracle.com/en/cloud/saas/planning-budgeting-cloud/pfusa/ mapping_unmapped_dimensions.html
NEW QUESTION: 3
A company's policy requires employees to perform file transfers using protocols which encrypt traffic. You suspect some employees are still performing file transfers using unencrypted protocols because the employees don't like changes. You have positioned a network sniffer to capture traffic from the laptops used by employees in the data ingest department. Using Wireshark to examine the captured traffic, which command can be used as a display filter to find unencrypted file transfers?
A. tcp.port == 21 || tcp.port == 22
B. tcp.port == 21
C. tcp.port = 23
D. tcp.port != 21
Answer: B