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NEW QUESTION: 1
The team is in the process of validating that the quality plan for the project will measure sufficiently the product of the project. What are the team members doing?
A. Quality planning
B. Quality control
C. Quality management
D. Quality audit
Answer: D
NEW QUESTION: 2
A colleague is attempting to launch several new CloudFormation stacks, and receives the following error response:
What should be done to address the error?
A. Add a Pause to the CloudFormation templates.
B. Run the CloudFormation API calls from a larger Amazon EC2 instance.
C. Combine stack templates into one, and retry the CreateStack API call.
D. Add an exponential backoff between CreateStack API calls.
Answer: D
NEW QUESTION: 3
Your network contains an Active Directory domain named contoso.com. The domain contains five domain controllers.
You have a branch office that has a local support technician named Tech1. Tech1 installs Windows Server
2016 on a server named RODC1 in a workgroup.
You need Tech1 to deploy RODC1 as a read-only domain controller (RODC) in the contoso.com domain.
Which three actions should you perform? Each correct answer presents part of the solution.
A. Create an RODC computer account by using Active Administrative Center.
B. Instruct Tech1 to install the Active Directory Domain Services server role on RODC1.
C. Instruct Tech1 to run the Active Directory Domain Services Configuration Wizard.
D. Instruct Tech1 to run dcpromo.exe on RODC1.
E. Modify the permissions of the Domain Controllers organizational unit (OU).
Answer: B,C,D
NEW QUESTION: 4
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
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Aalk - 2014-05-05 16:45:18
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