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NEW QUESTION: 1
A vRealize Automation administrator needs to allow users to revert their machines to their initial deployment state.
What should the administrator do?
A. Enable the Snapshot option in the blueprint.
B. Enable the Linked Clone option in the blueprint.
C. Enable the Reprovision option in the blueprint.
D. Enable the Destroy option in the blueprint.
Answer: C
Explanation:
Explanation/Reference:
Explanation:
https://docs.vmware.com/en/vRealize-Automation/7.0/com.vmware.vrealize.automation.doc/GUID-
8FF3AF1C-E21A-4562-AC54-28F85153EEC4.html

NEW QUESTION: 2



A. Yes
B. No
Answer: A

NEW QUESTION: 3
You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features.
You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels.
You create the following Python data frames:
You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: PCA(n_components = 10)
Need to reduce the dimensionality of the feature set to 10 features in both training and testing sets.
Example:
from sklearn.decomposition import PCA
pca = PCA(n_components=2) ;2 dimensions
principalComponents = pca.fit_transform(x)
Box 2: pca
fit_transform(X[, y])fits the model with X and apply the dimensionality reduction on X.
Box 3: transform(x_test)
transform(X) applies dimensionality reduction to X.
References:
https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html

NEW QUESTION: 4
攻撃者が別のゲストを介してハイパーバイザーと対話するのを防ぐために、次のうちどれを実装する必要がありますか？
A. コンテナ
B. 仮想デスクトップ
C. セキュリティブローカー
D. VMエスケープ保護
Answer: D