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NEW QUESTION: 1
データモデリング言語の使用方法
A. 変更できない有限で明確なネットワーク要素を表すため。
B. データを簡単に構造化、グループ化、検証、および複製できるようにするため
C. スクリプト言語を人間が読みやすくするため
D. インフラストラクチャ内の非構造化データのフローをモデル化します。
Answer: C
Explanation:
NEW QUESTION: 2
What is a role of a manager using a Kaizen circle for problem solving?
A. Encourage circle formation and checks progress
B. Recomend and implement solutions
C. Provide problem-solving training if requested
D. Provide technical or administrative service
Answer: A
NEW QUESTION: 3
データの視覚化要件に従って、診断テストの評価用に視覚化を作成する必要があります。
どの3つのモジュールを順番に使用することをお勧めしますか？回答するには、適切なモジュールをモジュールのリストから回答エリアに移動し、正しい順序で並べます。
Answer:
Explanation:
Explanation
Step 1: Sweep Clustering
Start by using the "Tune Model Hyperparameters" module to select the best sets of parameters for each of the models we're considering.
One of the interesting things about the "Tune Model Hyperparameters" module is that it not only outputs the results from the Tuning, it also outputs the Trained Model.
Step 2: Train Model
Step 3: Evaluate Model
Scenario: You need to provide the test results to the Fabrikam Residences team. You create data visualizations to aid in presenting the results.
You must produce a Receiver Operating Characteristic (ROC) curve to conduct a diagnostic test evaluation of the model. You need to select appropriate methods for producing the ROC curve in Azure Machine Learning Studio to compare the Two-Class Decision Forest and the Two-Class Decision Jungle modules with one another.
References:
http://breaking-bi.blogspot.com/2017/01/azure-machine-learning-model-evaluation.html