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NEW QUESTION: 1
In the EMS subsystem, a consumer distributor________.
A. sends EMS messages to an application
B. selects EMS messages to be discarded without the use of a filter
C. sends EMS messages to a disk file
D. forwards EMS messages to a remote system
Answer: A

NEW QUESTION: 2
Which two are primary concerns for a service-oriented architecture (SOA)?
A. Low cohesion
B. Loose coupling
C. Well defined contracts
D. Session handling
Answer: B,C

NEW QUESTION: 3
10,000個のデータポイントと150個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％をトレーニングに使用し、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、フィーチャセットの次元を10フィーチャ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、回答エリア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には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: 4
Drag drop the descriptions from the left onto the correct configuration-management technologies on the right.

Answer:
Explanation: