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NEW QUESTION: 1
Information collected on the status of project activities being performed to accomplish the project work is known as what?
A. Variance analysis
B. Work breakdown structure
C. Project management information system
D. Work performance information
Answer: D
Explanation:
Work Performance Information
Part of the executed project management plan includes the routine collection of work performance information. The information gathered is important, and is useful as input data for quality control measures and programs. It is also useful when audits, quality reviews, and process analyses are conducted. This is especially true of work performance information collected which includes technical performance measures, project deliverables status, required corrective actions, and performance reports. Pertinent work performance Information is essential to the project management plan and includes, but is not limited to:
* Status information on schedule progress.
* Whether deliverables have been completed, or not.
* Start and finish status of schedule activities.
* Quality standards expectation results.
* Authorized costs vs. costs incurred to date.
* Estimated completion time for scheduled activities in progress.
* Percentage of physical completion of in-progress schedule activities.
* Experience based knowledge acquired, documented, and posted to knowledge base.
* Details of resource utilization.
Gathering and analysis of work performance information is essential to the project management plan and should be considered a priority. Work performance information contributes to the efficient use of resources, identifies potential trouble spots and problems, and serves as an effective project management tool. This term is defined in the 3rd and the
4th edition of the PMBOK.

NEW QUESTION: 2
A company wants to leverage their cloud object storage account and move their long-term retention backups from their Dell EMC IDPA DP5300. What is a recommended solution?
A. License the Data Domain Cloud DR feature on the DP5300
B. Add the Cloud Tier metadata shelves to the DP5300 and then add the Data Domain Cloud Tier license
C. Upgrade to a DP5800 and then add the Data Domain Cloud Tier license
D. Configure a CloudBoost virtual or physical appliance to move long-term retention backups to the cloud object storage
Answer: A

NEW QUESTION: 3
トレーニングと検証のエラー値に大きな差があるモデルがあります。
新しいモデルを作成し、相互検証を実行する必要があります。
Azure Machine Learning Studioを使用して、新しいモデルのパラメーターセットを識別する必要があります。
各ステップで使用するモジュールはどれですか？答えるには、適切なモジュールを正しい手順にドラッグします。
各モジュールは、1回または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。コンテンツを表示するには、ペイン間で分割バーをドラッグするか、スクロールする必要がある場合があります。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: Split data
Box 2: Partition and Sample
Box 3: Two-Class Boosted Decision Tree
Box 4: Tune Model Hyperparameters
Integrated train and tune: You configure a set of parameters to use, and then let the module iterate over multiple combinations, measuring accuracy until it finds a "best" model. With most learner modules, you can choose which parameters should be changed during the training process, and which should remain fixed.
We recommend that you use Cross-Validate Model to establish the goodness of the model given the specified parameters. Use Tune Model Hyperparameters to identify the optimal parameters.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample