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NEW QUESTION: 1
You are solving a classification task.
The dataset is imbalanced.
You need to select an Azure Machine Learning Studio module to improve the classification accuracy.
Which module should you use?
A. Permutation Feature Importance
B. Synthetic Minority Oversampling Technique (SMOTE)
C. Fisher Linear Discriminant Analysis.
D. Filter Based Feature Selection
Answer: B
Explanation:
Explanation
Use the SMOTE module in Azure Machine Learning Studio (classic) to increase the number of underepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.
You connect the SMOTE module to a dataset that is imbalanced. There are many reasons why a dataset might be imbalanced: the category you are targeting might be very rare in the population, or the data might simply be difficult to collect. Typically, you use SMOTE when the class you want to analyze is under-represented.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote

NEW QUESTION: 2
Which statement is true regarding trial versions?
A. IBM Spectrum Protect Plus trial version includes a license key for IBM Spectrum Protect Extended Edition.
B. A license key can be downloaded through Passport Advantage to upgrade from the trial version to the full paid version.
C. The trial version of IBM Spectrum Protect Plus is good for 90 days before upgrading to the paid version is required.
D. The trial version must be uninstalled before upgrading to the full paid version so that it can be properly licensed.
Answer: B

NEW QUESTION: 3
An organization has developed a major application that has undergone accreditation testing. After receiving the results of the evaluation, what is the final step before the application can be accredited?
A. Acceptance of risk by the authorizing official
B. Adoption of standardized policies and procedures
C. Approval of the System Security Plan (SSP)
D. Remediation of vulnerabilities
Answer: A