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NEW QUESTION: 1

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

NEW QUESTION: 2
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

NEW QUESTION: 3
Which of the following is one of the fundamental principles identified in the CIMA Code of Ethics?
A. Professional consideration and due care
B. Professional cooperation and due care
C. Professional conscience and due care
D. Professional competence and due care
Answer: D

NEW QUESTION: 4
FlexVPNトンネルでは、どの構成構成要素を使用する必要がありますか？
A. EAP設定
B. マルチポイントGREトンネルインターフェイス
C. IKEv1ポリシー
D. IKEv2プロファイル
Answer: D