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NEW QUESTION: 1
Which restriction will prevent you from copying a server profile from one server to another?
A. The server processor count is different.
B. The server has a different network adapter layout
C. The server has additional memory.
D. The server BIOS settings are a different version than the settings on the original.
Answer: B

NEW QUESTION: 2
A 14-year-old teenager is demonstrating behavior indicative of an obsessive-compulsive disorder. She is obsessed with her appearance. She will not leave her room until her hair, clothes, and makeup are perfect.
She always dresses immaculately. Recently, she expressed disgust over her appearance after she gained
5 lb. After observing a marked weight loss over a 2-week period, her mother suspects that she is experiencing bulimia. She eats everything on her plate, then runs to the bathroom. In interviewing the teenager, she discusses in great detail all of the events leading to her bulimia, but not her feelings. What defense mechanism is she using?
A. Intellectualization
B. Dissociation
C. Rationalization
D. Displacement
Answer: A
Explanation:
Explanation/Reference:
Explanation:
(A) Dissociation is separating a group of mental processes from consciousness or identity, such as multiple personalities. That is not evident in this situation. (B) Intellectualization is excessive use of reasoning, logic, or words usually without experiencing associated feelings. This is the defense mechanism that this client is using. (C) Rationalization is giving a socially acceptable reason for behavior rather than the actual reason. She is discussing events, not reasons. (D) Displacement is a shift of emotion associated with an anxiety-producing person, object, or situation to a less threatening object.

NEW QUESTION: 3
機械学習タスクを適切なシナリオに一致させます。
答えるには、適切なタスクを左側の列から右側のシナリオにドラッグします。各タスクは、1回使用することも、複数回使用することも、まったく使用しないこともできます。
注：正しい選択はそれぞれ1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: Model evaluation
The Model evaluation module outputs a confusion matrix showing the number of true positives, false negatives, false positives, and true negatives, as well as ROC, Precision/Recall, and Lift curves.
Box 2: Feature engineering
Feature engineering is the process of using domain knowledge of the data to create features that help ML algorithms learn better. In Azure Machine Learning, scaling and normalization techniques are applied to facilitate feature engineering. Collectively, these techniques and feature engineering are referred to as featurization.
Note: Often, features are created from raw data through a process of feature engineering. For example, a time stamp in itself might not be useful for modeling until the information is transformed into units of days, months, or categories that are relevant to the problem, such as holiday versus working day.
Box 3: Feature selection
In machine learning and statistics, feature selection is the process of selecting a subset of relevant, useful features to use in building an analytical model. Feature selection helps narrow the field of data to the most valuable inputs. Narrowing the field of data helps reduce noise and improve training performance.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml

NEW QUESTION: 4
You are debugging a model that you havebuilt. When you run it, you receive the generator error for Variable Z shown below:
Variable Z: No IIP value can be set for this variable. It is formula could not be used and none of the program is inputs supplied a value.
What are two causes for the error? (Choose two.)
A. Variable Z should be a non-portfolio variable but the portfolio property is set to yes.
B. Variable Z should be portfolio but has not been initialized properly anywhere.
C. Variable Z has it's aggregates property set to "Yes" and it should be "No".
D. Variable Z is included in an initialization module as well as the data.
Answer: A,B

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