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NEW QUESTION: 1
特徴抽出方法を選択する必要があります。
どの方法を使用する必要がありますか？
A. ケンドール相関
B. ムードの中央値検定
C. 相互情報
D. 順列機能の重要性
Answer: A
Explanation:
In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's tau coefficient (after the Greek letter t), is a statistic used to measure the ordinal association between two measured quantities.
It is a supported method of the Azure Machine Learning Feature selection.
Scenario: When you train a Linear Regression module using a property dataset that shows data for property prices for a large city, you need to determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. You must ensure that the distribution of the features across multiple training models is consistent.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules

NEW QUESTION: 2
SIMULATION
A prescription for duragesic patches should be filed under which DEA schedule?
Answer:
Explanation:
Schedule II

NEW QUESTION: 3
入出力フィールドで外部キーチェックが実行されるのはいつですか？
A. フィールドが、検索ヘルプが定義されている辞書フィールドを参照する場合
B. フィールドが追加検索が定義されている辞書フィールドを参照する場合
C. フィールドが、チェックテーブルが定義されている辞書フィールドを参照する場合
D. フィールドが値ヘルプが定義されている辞書フィールドを参照する場合
Answer: C

NEW QUESTION: 4

A. Option D
B. Option B
C. Option C
D. Option A
E. Option E
Answer: B,D,E