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NEW QUESTION: 1
비용 추정에 도움이되는 AWS 도구는 무엇입니까? (3 개 선택)
A. AWS 총 소유 비용 (TCO) 계산기
B. AWS 월간 간편 계산기
C. 비용 추정기
D. 세부 결제 보고서
E. 비용 할당 태그
Answer: A,B,E
Explanation:
Explanation
https://aws.amazon.com/premiumsupport/knowledge-center/estimating-aws-resource-costs/
NEW QUESTION: 2
This question requires that you evaluate the underlined text to determine if it is correct.
The "ExFAT" file system can automatically verify and auto correct data to avoid file system errors.
Instructions: Review the underlined text. If it makes the statement correct, select "No change is needed". If the statement is incorrect, select the answer choice than makes the statement correct.
A. No change is needed
B. FAT32
C. NTFS
D. ReFS
Answer: D
Explanation:
Explanation
Resilient File System (ReFS) is a Microsoft proprietary file system introduced with Windows Server 2012 with the intent of becoming the "next generation" file system after NTFS. ReFS key design advantages are intended to include automatic integrity checking and data scrubbing, removing the need for chkdsk and protecting against data degradation.
NEW QUESTION: 3
Before accurate statistical troubleshooting with a wireless protocol analyzer can be performed on a wireless LAN, which of the following must be completed?
A. Traffic injection analysis
B. Directional traffic filtering
C. Quality of Service (QoS) design
D. Operational traffic policy
E. Baseline traffic analysis
Answer: E
NEW QUESTION: 4
You are building a regression model tot estimating the number of calls during an event.
You need to determine whether the feature values achieve the conditions to build a Poisson regression model.
Which two conditions must the feature set contain? I ach correct answer presents part of the solution. NOTE:
Each correct selection is worth one point.
A. The label data must be non discrete.
B. The data must be whole numbers.
C. The label data can be positive or negative,
D. The label data must be a positive value
E. The label data must be a negative value.
Answer: B,D
Explanation:
Explanation
Poisson regression is intended for use in regression models that are used to predict numeric values, typically counts. Therefore, you should use this module to create your regression model only if the values you are trying to predict fit the following conditions:
* The response variable has a Poisson distribution.
* Counts cannot be negative. The method will fail outright if you attempt to use it with negative labels.
* A Poisson distribution is a discrete distribution; therefore, it is not meaningful to use this method with non-whole numbers.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/poisson-regression
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