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NEW QUESTION: 1
Consider two bonds, X and Y. Both bonds presently are selling at their par value of Rs.1000. Each pays interest of Rs.150 annually. Bond X will mature in 6 years while bond Y will mature in 7 years. If the yields to maturity on the two bonds decrease from 15% to 12%:
A. Both bonds will increase in value, but bond Y will increase more than bond X
B. Both bonds will decrease in value, but bond Y will decrease more than bond X
C. Both bonds will increase in value, but bond X will increase more than bond Y
D. Both bonds will decrease in value, but bond X will decrease more than bond Y
Answer: A
NEW QUESTION: 2
ある会社がアプリケーションロードバランサーの背後にあるAmazonCC2インスタンスでWebサービスを実行しているインスタンスは、2つのアベイラビリティーゾーンにまたがるAmazon EC2 Auto Scalingグループで実行されています。会社は、必要なサービスレベルアグリーメント（SLA）を満たすために、最小限のツアーインスタンスが必要です。 ）コストを低く抑えながらアベイラビリティーゾーンが終了した場合、会社はどのようにしてSLAに準拠し続けることができますか？
A. Auto Scalingグループを変更して、3つのアベイラビリティーゾーンにまたがる6台のサーバーを使用する
B. Auto Scalingグループを変更して、2つのアベイラビリティーゾーンにまたがる8台のサーバーを使用する
C. より大きなインスタンスタイプを使用するようにAutoScalingグループの起動構成を変更します
D. クールダウン期間が短いターゲットトラッキングスケーリングポリシーを追加します
Answer: B
NEW QUESTION: 3
You are analyzing a raw dataset that requires cleaning.
You must perform transformations and manipulations by using Azure Machine Learning Studio.
You need to identify the correct modules to perform the transformations.
Which modules should you choose? To answer, drag the appropriate modules to the correct scenarios. Each module may be used once, more than once, or not at all.
You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Clean Missing Data
Box 2: SMOTE
Use the SMOTE module in Azure Machine Learning Studio to increase the number of underepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.
Box 3: Convert to Indicator Values
Use the Convert to Indicator Values module in Azure Machine Learning Studio. The purpose of this module is to convert columns that contain categorical values into a series of binary indicator columns that can more easily be used as features in a machine learning model.
Box 4: Remove Duplicate Rows
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/convert-to-indicator-values
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