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NEW QUESTION: 1
10,000のデータポイントと150の特徴を持つ正規化された数値特徴セットを含むマルチクラス分類タスク用に作成されたデータセットがあります。
データポイントの75％をトレーニングに、25％をテストに使用します。 Pythonでscikit-learn機械学習ライブラリを使用しています。 Xを使用して機能セットを示し、Yを使用してクラスラベルを示します。
次のPythonデータフレームを作成します。

主成分分析（PCA）メソッドを適用して、トレーニングセットとテストセットの両方で、機能セットの次元数を10の機能に減らす必要があります。
コードセグメントをどのように完成させる必要がありますか？回答するには、回答領域で適切なオプションを選択します。
注：それぞれの正しい選択は1ポイントの価値があります。

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: 2
Drag and drop the features of IP operations from the left onto the correct descriptions on the right.

Answer:
Explanation:

NEW QUESTION: 3
When is a mask used to limit access to data in a table?
A. When label-based access control (LBAC) is used to protect the table.
B. When row and column access control (RCAC) is used to protect the table.
C. When discretionary access control (DAC) is used to protect the table.
D. When mandatory access control (MAC) is used to protect the table.
Answer: B
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 4
Click the Exhibit button.

Which statement is true about the output shown in the exhibit?
A. The OSPF interface is using the default priority.
B. The OSPF interface is using md5 authentication.
C. The BDR address is 1.1.1.1.
D. The BDR address is 25.0.0.25.
Answer: C