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NEW QUESTION: 1
다음 중 데이터 마이닝 활동이 민감한 데이터를 드러내지 않도록 하기 위해 사용되는 것은 무엇입니까?
A. 데이터베이스를 전처리하여 inn ......이 학습 된 패턴에서 공개 될 수 있는지 확인합니다.
B. 필드 수준에서 데이터를 암호화하고 암호화 키를 엄격하게 제어합니다.
C. 기본 인프라에서 2 단계 인증을 구현합니다.
D. 적은 수의 사용자가 데이터베이스에 액세스 할 수 있도록 데이터 요소에 대한 최소 권한 원칙을 구현합니다.
Answer: D

NEW QUESTION: 2
Der Kunde Kim hat eine kostengünstige Netzwerklösung angefordert, um die Büroräume nach Bedarf neu konfigurieren zu können. Welche Netzwerklösung bietet die BESTE Lösung?
A. Drahtlose Zugangspunkte
B. Virtuelle lokale Netzwerke
C. Private IP-Adressierung
D. Wide Area Networking
Answer: A

NEW QUESTION: 3
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/