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NEW QUESTION: 1
Consider the following Nmap output:

what command-line parameter could you use to determine the type and version number of the web server?
A. -sv
B. -Pn
C. -V
D. -ss
Answer: D

NEW QUESTION: 2
In which of the team development stages are the teams interdependent and work through issues smoothly and effectively?
A. Norming
B. Forming
C. Performing
D. Storming
Answer: C

NEW QUESTION: 3
Azure Machine Learning Studioで実験を作成します。 10,000行を含むトレーニングデータセットを追加します。最初の9,000行はクラス0（90パーセント）を表します。
残りの1,000行はクラス1（10パーセント）を表します。
トレーニングセットは、2つのクラス間の不均衡です。 5つのデータ行を使用して、クラス1のトレーニング例の数を4,000に増やす必要があります。 Synthetic Minority Oversampling Technique（SMOTE）モジュールを実験に追加します。
モジュールを構成する必要があります。
どの値を使用する必要がありますか？回答するには、回答領域のダイアログボックス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: 300
You type 300 (%), the module triples the percentage of minority cases (3000) compared to the original dataset (1000).
Box 2: 5
We should use 5 data rows.
Use the Number of nearest neighbors option to determine the size of the feature space that the SMOTE algorithm uses when in building new cases. A nearest neighbor is a row of data (a case) that is very similar to some target case. The distance between any two cases is measured by combining the weighted vectors of all features.
By increasing the number of nearest neighbors, you get features from more cases.
By keeping the number of nearest neighbors low, you use features that are more like those in the original sample.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote

NEW QUESTION: 4
新しいプロジェクトには、さまざまな部門の特定のスキルと能力を持つリソースが必要です。ほとんどの会社のスタッフはすでに他のプロジェクトマネージャーに割り当てられているため、利用可能な社内の人材を特定して同意し、外部の専門家を雇う必要があります。
プロジェクトマネージャーは、リソースを取得するために最初に何を使用する必要がありますか？
A. 要件分析ツール
B. 個人およびチームの評価
C. 交渉スキル
D. 獲得スキル
Answer: C