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NEW QUESTION: 1
You are developing a linear regression model in Azure Machine Learning Studio. You run an experiment to compare different algorithms.
The following image displays the results dataset output:

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the image.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Boosted Decision Tree Regression
Mean absolute error (MAE) measures how close the predictions are to the actual outcomes; thus, a lower score is better.
Box 2:
Online Gradient Descent: If you want the algorithm to find the best parameters for you, set Create trainer mode option to Parameter Range. You can then specify multiple values for the algorithm to try.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression

NEW QUESTION: 2
開発者は、人々が雇用主に関連することを可能にするアプリケーションの拡張を作成しています。
要件を満たすための最も簡単なソリューションを提供するデータモデルはどれですか。
A. 主従関係を介して多くの人を多くの人に関連付けるための接合オブジェクトを作成します
B. 個人に雇用主がいることを示す主従関係を作成する
C. ジャンクションオブジェクトを作成して、ルックアップ関係を介して多くの人を多くの人に関連付ける
D. 個人が雇用主を持っていることを示すために、ルックアップエリアシップを作成します
Answer: B

NEW QUESTION: 3
SANとLANの物理接続を1つのレイヤー2プロトコルだけで統合できるようにするには、次のどのストレージ接続タイプを使用する必要がありますか？
A. ファイバーチャネル
B. FCoE
C. SCSI
D. T1 / E1
Answer: B

NEW QUESTION: 4
Which two preference definitions determines the default values during the collection process?
A. Default aging method
B. Default contact for unknown dunning recipients
C. Preference set
D. Default exchange rate
E. Display of open transactions
Answer: B,D
Explanation:
Reference: Oracle Fusion Applications Financials Implementation Guide , Manage Collections Preferences