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NEW QUESTION: 1
HOTSPOT
You need to plan the Atlanta farm deployment.
Which file systems should you use? To answer, select the appropriate file system from each list in the answer area.

Answer:
Explanation:

NEW QUESTION: 2
Which of the following statements is wrong about firewall bandwidth policy?
A. In the same set of parent-child policies, the same bandwidth channel cannot be referenced.
B. For maximum bandwidth and the number of connections limit, the sub-policy cannot be greater than the parent policy.
C. If bandwidth management and source NAT are used at the same time, specify the address before conversion when configuring source address/region matching conditions for bandwidth policy.
D. If bandwidth management and source NAT are used at the same time, specify the address after conversion when configuring source address/region matching conditions for the bandwidth policy.
Answer: D

NEW QUESTION: 3
You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).
The remaining 1,000 rows represent class 1 (10 percent).
The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.
You need to configure the module.
Which values should you use? 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:
Box 1: 300
You type 300 (%), the module triples the percentage of minority cases (3000) compared to the original dataset (1000).
Box 2: 5
We should use 5 data rows.
Use the Number of nearest neighbors option to determine the size of the feature space that the SMOTE algorithm uses when in building new cases. A nearest neighbor is a row of data (a case) that is very similar to some target case. The distance between any two cases is measured by combining the weighted vectors of all features.
By increasing the number of nearest neighbors, you get features from more cases.
By keeping the number of nearest neighbors low, you use features that are more like those in the original sample.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote

NEW QUESTION: 4
What is the purpose of the storage bin field in the "Warehouse Mgmt 2" view of the material master?
A. To identify the bulk storage bin for that material in the storage type
B. To identify the fixed storage bin for that material in the storage type
C. To identify the next empty storage bin for that material in the storage type
D. To identify the open storage bin for that material in the storage type
Answer: B