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NEW QUESTION: 1
Azure Machine Learning Studioを使用して実験を作成しています。
評価のためにデータを4つのサブセットに分割する必要があります。データには高度な欠損値があります。
分析用のデータを準備する必要があります。
実験を作成するための適切な方法を選択する必要があります。
どの3つのモジュールを順番に実行する必要がありますか？回答するには、適切なアクションをアクションのリストから回答エリアに移動し、正しい順序に並べます。
注：回答の選択肢の複数の順序が正しいです。選択した正しい注文のいずれかのクレジットを受け取ります。
Answer:
Explanation:
Explanation:
The Clean Missing Data module in Azure Machine Learning Studio, to remove, replace, or infer missing values.
Incorrect Answers:
Latent Direchlet Transformation: Latent Dirichlet Allocation module in Azure Machine Learning Studio, to group otherwise unclassified text into a number of categories. Latent Dirichlet Allocation (LDA) is often used in natural language processing (NLP) to find texts that are similar. Another common term is topic modeling.
Build Counting Transform: Build Counting Transform module in Azure Machine Learning Studio, to analyze training data. From this data, the module builds a count table as well as a set of count-based features that can be used in a predictive model.
Missing Value Scrubber: The Missing Values Scrubber module is deprecated.
Feature hashing: Feature hashing is used for linguistics, and works by converting unique tokens into integers.
Replace discrete values: the Replace Discrete Values module in Azure Machine Learning Studio is used to generate a probability score that can be used to represent a discrete value. This score can be useful for understanding the information value of the discrete values.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data
NEW QUESTION: 2
HTTPSサーバーは、管理のためにルーターで構成されます。どのコマンドがルーターのリスニングポートを443から444に変更しますか？
A. ip https secure-port 444
B. ip http secure-server 444
C. ip http secure-port 444
D. ip http server secure-port 444
Answer: C
NEW QUESTION: 3
Which product is best suited to passively monitor a business process?
A. TIBCO ActiveMatrix BPM
B. TIBCO ActiveMatrix Service Bus
C. TIBCO ActiveMatrix BusinessEvents
D. TIBCO ActiveMatrix BusinessWorks
Answer: C
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