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NEW QUESTION: 1
True or False: XMPP Management is enabled by default.
A. TRUE
B. FALSE
Answer: B
Explanation:
Explanation/Reference:
Reference: https://www.arista.com/en/um-eos-4172f/eos-section-2-5-session-management- commands#ww1129609
NEW QUESTION: 2
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You train a classification model by using a logistic regression algorithm.
You must be able to explain the model's predictions by calculating the importance of each feature, both as an overall global relative importance value and as a measure of local importance for a specific set of predictions.
You need to create an explainer that you can use to retrieve the required global and local feature importance values.
Solution: Create a MimicExplainer.
Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Instead use Permutation Feature Importance Explainer (PFI).
Note 1: Mimic explainer is based on the idea of training global surrogate models to mimic blackbox models. A global surrogate model is an intrinsically interpretable model that is trained to approximate the predictions of any black box model as accurately as possible. Data scientists can interpret the surrogate model to draw conclusions about the black box model.
Note 2: Permutation Feature Importance Explainer (PFI): Permutation Feature Importance is a technique used to explain classification and regression models. At a high level, the way it works is by randomly shuffling data one feature at a time for the entire dataset and calculating how much the performance metric of interest changes. The larger the change, the more important that feature is. PFI can explain the overall behavior of any underlying model but does not explain individual predictions.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-machine-learning-interpretability
NEW QUESTION: 3
Which of the following do you have to consider when you configure the "quotation ? sales order" sales process? (Choose two)
A. Define the Target Item Category in copying control for all manually maintained item categories in the quotation.
B. Set up the item category of the quotation so that it has an incompletion procedure for a value item.
C. Define the completion rule in the item category of the quotation as not relevant for completion.
D. Specify how pricing data should be handled when copying items.
Answer: A,D