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NEW QUESTION: 1
You are running a large logistic regression for 1,000 feature variables by using the LoisticRegression() function in the MicrosoftML package. All of the predictor variables are numeric.
Currently, you specify the input variables separately by using the following formula.
Outcome ~ Feature000 + Feature001 + Feature002 + ... + Feature999
You discover that it takes 20 minutes to estimate each model.
You need to reduce the amount of time required to estimate each model without losing any information in the predictors.
What should you do?
A. Use princomp() on the correlation matrix of Features, and then use only the first 100 principle components to reduce the number of input variables.
B. Use selectFeatures() to select the features that provide the most information about the outcome variable.
C. Use stepControl() to perform stepwise regression to limit the number of variables that contribute to the model.
D. Use concat() to create a single array variable named Features, and then specify a new formula named Outcome ~ Features.
Answer: D

NEW QUESTION: 2
あなたはあなたの会社のデータエンジニアです。アプリケーションは、NoSQLデータベースを使用してデータを保存します。データベースは、Key-ValueおよびワイドカラムのNoSQLデータベースタイプを使用します。
開発者は、APIを使用してデータベース内のデータにアクセスする必要があります。
データベースのモデルとタイプに使用するAPIを決定する必要があります。
どちらのAPIを使用する必要がありますか？それぞれの正解は完全な解決策を提示します。
注：それぞれの正しい選択は1ポイントに相当します。
A. Gremlin API
B. Cassandra API
C. テーブルAPI
D. SQL API
E. MongoDB API
Answer: B,E
Explanation:
B：Azure Cosmos DBは、ミッションクリティカルなアプリケーション向けのMicrosoftのグローバルに分散されたマルチモデルデータベースサービスです。これはマルチモデルデータベースであり、ドキュメント、キー値、グラフ、および列データモデルをサポートしています。
E：ワイド列ストアは、データを行ではなく列として一緒に格納し、大規模なデータセットに対するクエリ用に最適化されます。最も人気のあるのは、CassandraとHBaseです。
参照：
https://docs.microsoft.com/en-us/azure/cosmos-db/graph-introduction
https://www.mongodb.com/scale/types-of-nosql-databases

NEW QUESTION: 3
DRAG DROP
Drag into proper boxes.

Answer:
Explanation:

NEW QUESTION: 4
If you cross-certify a CA, you trust the CA to issue certificates to users and servers based onwhich part of a name tree?
A. Compliant
B. Lower
C. Standard
D. Higher
Answer: B