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NEW QUESTION: 1

Router(config)# router ospf 1
Router(config-router)# network 10.0.0.0 255.0.0.0 area 0

A. Option A
B. Option E
C. Option C
D. Option F
E. Option D
F. Option B
Answer: C
Explanation:
When configuring OSPF, the mask used for the network statement is a wildcard mask similar to an access list. In this specific example, the correct syntax would have been "network 10.0.0.0 0.0.0.255 area 0."

NEW QUESTION: 2
Siehe Ausstellung.

Router R1 Fa0 / 0 kann Router P3 Fa0 / 1 nicht anpingen.
Welche Aktion muss in Router R1 ausgeführt werden, um das Konfigurationsproblem zu beheben?
A. Konfigurieren Sie eine statische Route mit 10.10.10.2 als nächstem Hop, um das Netzwerk 20.20.20.0/24 zu erreichen
B. Legen Sie das Standardnetzwerk auf 20.20.20.0/24 fest
C. Konfigurieren Sie eine statische Route mit Fa0 / 1 als Ausgangsschnittstelle, um das Netzwerk 20.20.20.0/24 zu erreichen
D. Legen Sie das Standard-Gateway auf 20.20.20.2 fest
Answer: A

NEW QUESTION: 3
You need to select a feature extraction method.
Which method should you use?
A. Kendall correlation
B. Mood's median test
C. Mutual information
D. Permutation Feature Importance
Answer: A
Explanation:
In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's tau coefficient (after the Greek letter), is a statistic used to measure the ordinal association between two measured quantities.
It is a supported method of the Azure Machine Learning Feature selection.
Scenario: When you train a Linear Regression module using a property dataset that shows data for property prices for a large city, you need to determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. You must ensure that the distribution of the features across multiple training models is consistent.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules

NEW QUESTION: 4



A. 0
B. 1
C. 2
D. 3
Answer: A
Explanation:
As we can see at the top we have 14vCPUs, 7VMs. So we have 14 vCPUs to distribute between the 7 VMs. I've broken down my thought process into several steps after looking for hints: Now, seeing how high RDY is we definately get a hint that FileSever01 is overprovisioned. Add a value of 9.28 of %CSTP to the equation and that is definitely the case. In fact, with such a huge %CSTP I would guess that it is overprovisioned 8:1, meaning that it probably has a 8vcpus.
Both scenarios 1 and 2 have a total of 14 vCPUs. However, due to the fact of %CSTP of being
9.28 I'd probably go with scenario 01 and say 8 vCPUs instead of 4vCPUs.