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NEW QUESTION: 1
What is the length of the Ethernet_II frame that contains the Ethernet header?
A. 60-1560B
B. 64-1500B
C. 64-1518B
D. 46-1500B
Answer: C
NEW QUESTION: 2
What is wrong with the collaboration occurrence shown in the exhibit?
A. Role bindings should be represented by dashed lines.
B. Client and Server role names should be underlined.
C. The <<ourrence>> keyword is missing.
D. The <<role>> keywords are missing.
E. The collaboration occurrence name should be underlined.
Answer: A
NEW QUESTION: 3
Which is the required object for Oracle Universal Records Management's file plan?
A. Record Series
B. Record Categories
C. Record Function
D. Record Folders
Answer: B
Explanation:
Explanation/Reference:
Explanation:
NEW QUESTION: 4
You need to select a feature extraction method.
Which method should you use?
A. Kendall correlation
B. Permutation Feature Importance
C. Mutual information
D. Mood's median test
Answer: A
Explanation:
In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's tau coefficient (after the Greek letter t), 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
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