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NEW QUESTION: 1
In the OSPF network, for the benefit of dividing the area, the following description is incorrect ()?
A. Reduce the complexity of running the SPF algorithm
B. Reduce the size of the LSDB
C. Conducive to routing for aggregation
D. Reduce entries for intra-area routes
Answer: D

NEW QUESTION: 2
Critics of monopolistic competition argue that it is inefficient because the firms
A. produce at an output that fails to minimize average total cost.
B. earn an abnormally high economic profit.
C. charge a price that exceeds average total cost when the market is in long-run equilibrium.
Answer: A
Explanation:
Since ATC>MC and firms operate where MC = MR and P = ATC in the long run, this implies that P>MC. So MC

NEW QUESTION: 3
あなたは銀行で働いているデータサイエンティストであり、Azure MLを使用して、顧客がローンを返済する可能性が高いかどうかを予測する機械学習モデルをトレーニングして登録しました。
モデルがどのように選択を行っているかを理解し、モデルが申請者の居住地に基づいてローンを拒否するなどの政府の規制に違反しないことを確認する必要があります。
顧客データの各機能が予測にどの程度影響を与えているかを判断する必要があります。
あなたは何をするべきか？
A. モデルとそのトレーニングデータセットのデータドリフトモニタリングを有効にします。
B. 解釈性パッケージを使用して、モデルの説明を生成します。
C. Hyperdriveライブラリを使用して、複数のハイパーパラメーター値でモデルをテストします。
D. 既知のラベル値を持ついくつかのテストデータに対してモデルをスコアリングし、その結果を使用して混同行列を計算します。
E. モデル登録にタグを追加して、トレーニングデータセットの特徴の名前を示します。
Answer: B
Explanation:
When you compute model explanations and visualize them, you're not limited to an existing model explanation for an automated ML model. You can also get an explanation for your model with different test data. The steps in this section show you how to compute and visualize engineered feature importance based on your test data.
Incorrect Answers:
A: In the context of machine learning, data drift is the change in model input data that leads to model performance degradation. It is one of the top reasons where model accuracy degrades over time, thus monitoring data drift helps detect model performance issues.
B: A confusion matrix is used to describe the performance of a classification model. Each row displays the instances of the true, or actual class in your dataset, and each column represents the instances of the class that was predicted by the model.
C: Hyperparameters are adjustable parameters you choose for model training that guide the training process. The HyperDrive package helps you automate choosing these parameters.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-machine-learning-interpretability-automl

NEW QUESTION: 4
At Tiny Toys Ltd, business analyst Sophie has been employed to investigate and improve the invoicing process. To help her understand the data required in the system, she intends to request and review a sample of completed invoices.
What elicitation technique will she be using?
A. Special purpose records
B. Observation
C. Activity sampling
D. Document analysis
Answer: D

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