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NEW QUESTION: 1
自動機械学習を使用して回帰モデルをトレーニングする予定です。欠損値のある特徴と、明確な値がほとんどないカテゴリー特徴を持つデータがあります。
トレーニングタスクの一部として、欠損値を自動的に代入し、カテゴリカル機能をエンコードするように自動機械学習を構成する必要があります。
AutoMLConfigクラスで使用するパラメーターと値のペアはどれですか。
A. exclude_nan_labels = True
B. task = 'classification'
C. featurization = 'auto'
D. enable_tf = True
E. enable_voting_ensemble = True
Answer: C
Explanation:
Featurization str or FeaturizationConfig
Values: 'auto' / 'off' / FeaturizationConfig
Indicator for whether featurization step should be done automatically or not, or whether customized featurization should be used.
Column type is automatically detected. Based on the detected column type preprocessing/featurization is done as follows:
Categorical: Target encoding, one hot encoding, drop high cardinality categories, impute missing values.
Numeric: Impute missing values, cluster distance, weight of evidence.
DateTime: Several features such as day, seconds, minutes, hours etc.
Text: Bag of words, pre-trained Word embedding, text target encoding.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.automlconfig

NEW QUESTION: 2
Stakeholder satisfaction should be managed as a key project:
A. Objective
B. Benefit
C. Initiative
D. Process
Answer: A

NEW QUESTION: 3
Ein Unternehmen stellt Microsoft 365 bereit.
Sie müssen den bedingten Zugriff implementieren, um den Zugriff auf Administratorkonten einzuschränken, wenn Benutzer sich an bestimmten Standorten authentifizieren.
Sie müssen die kostengünstigste Lizenz auswählen, die die Anforderung erfüllt.
Welche Lizenz sollten Sie wählen?
A. Azure Active Directory Premium P1
B. Azure Active Directory Premium P2
C. Azure Active Directory B2B
D. Azure Active Directory kostenlos
Answer: A
Explanation:
Explanation
Conditional access policies require an Azure AD Premium P1 license.