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NEW QUESTION: 1
-- Exhibit- -- Exhibit -

The diagram is an example of a(n):
A. Affinity Diagram
B. Process Map Diagram
C. Flowchart
D. Cause-and-Effect Diagram
E. Force Field Diagram
Answer: D

NEW QUESTION: 2
Welche der folgenden Aussagen wäre für einen IS-Prüfer, der während einer Finanzprüfung eine kritische Tabelle überprüft, von größter Bedeutung?
A. Zugriffsanforderungen werden manuell verarbeitet.
B. Änderungen an der Datei werden nicht immer dokumentiert.
C. Eine Kopie der aktuell validierten Datei ist nicht verfügbar.
D. Regelmäßige Zugriffsüberprüfungen werden manuell durchgeführt.
Answer: B

NEW QUESTION: 3
会社のAzureリソースを保護するソリューションを設計しています。この環境は10チームをホストしています。各チームはプロジェクトを管理し、プロジェクトマネージャー、仮想マシン（VM）オペレーター、開発者、および請負業者がいます。
プロジェクトマネージャーは、ユーザーのアクセスと認証を除くすべてを管理できる必要があります。 VMオペレーターはVMを管理できる必要がありますが、VMが接続されている仮想ネットワークまたはストレージアカウントは管理できません。
開発者と請負業者は、ストレージアカウントを管理できる必要があります。
各メンバーの役割を推奨する必要があります。
何をお勧めしますか？答えるには、適切な役割を正しい従業員タイプにドラッグします。各役割は、1回、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：各正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

NEW QUESTION: 4
x.1、x2、およびx3の機能に対してscikit-learn Pythonライブラリを使用して、機能のスケーリングを実行しています。
元のデータとスケーリングされたデータを次の図に示します。

ドロップダウンメニューを使用して、グラフィックに表示される情報に基づいて各質問に回答する回答選択肢を選択します。
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: StandardScaler
The StandardScaler assumes your data is normally distributed within each feature and will scale them such that the distribution is now centred around 0, with a standard deviation of 1.
Example:
All features are now on the same scale relative to one another.
Box 2: Min Max Scaler
Notice that the skewness of the distribution is maintained but the 3 distributions are brought into the same scale so that they overlap.
Box 3: Normalizer
References:
http://benalexkeen.com/feature-scaling-with-scikit-learn/