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NEW QUESTION: 1

A. Option C
B. Option E
C. Option D
D. Option B
E. Option A
Answer: B,C,D

NEW QUESTION: 2
Azure Machine Learning Studioで新しい実験を作成しています。多くの列に欠損値がある小さなデータセットがあります。データでは、各列に予測変数を適用する必要はありません。欠損データの処理モジュールを使用して、欠損データを処理する予定です。
データクリーニング方法を選択する必要があります。
どの方法を使用する必要がありますか？
A. MICEを使用して交換
B. 合成マイノリティオーバーサンプリングテクニック（SMOTE）
C. を使用して置き換えます。確率的PCA
D. 正規化
Answer: C
Explanation:
Explanation
Replace using Probabilistic PCA: Compared to other options, such as Multiple Imputation using Chained Equations (MICE), this option has the advantage of not requiring the application of predictors for each column. Instead, it approximates the covariance for the full dataset. Therefore, it might offer better performance for datasets that have missing values in many columns.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

NEW QUESTION: 3
A financial service company is running distributed computing software to manage a fleet of 20 servers for their calculations. There are 2 control nodes and 18 worker nodes to run the calculations. Worker nodes can be automatically started by the control nodes when required.
Currently, all nodes are running on demand, and the worker nodes are used for approximately 4 hours each day.
Which combination of actions will be MOST cost-effective? (Choose two.)
A. Use Spot Instances for the worker nodes and On-Demand Instances if there is no Spot availability.
B. Use Reserved Instances for the worker nodes.
C. Use Dedicated Hosts for the control nodes.
D. Use Reserved Instances for the control nodes.
E. Use Spot Instances for the control nodes and On-Demand Instances if there is no Spot availability.
Answer: B,E

NEW QUESTION: 4
You define a Contract Identification Rule that uses the following source document attributes to match transaction lines:
Bill-to Customer Party Identifier
Extensible Header Character Attribute 4
Based the data displayed:

How many contracts will be created in Revenue Management?
A. 0
B. 1
C. 2
D. 3
E. 4
Answer: D