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NEW QUESTION: 1
You need to identify the methods for dividing the data according to the testing requirements.
Which properties should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Scenario: Testing
You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio.
Box 1: Assign to folds
Use Assign to folds option when you want to divide the dataset into subsets of the data. This option is also useful when you want to create a custom number of folds for cross-validation, or to split rows into several groups.
Not Head: Use Head mode to get only the first n rows. This option is useful if you want to test a pipeline on a small number of rows, and don't need the data to be balanced or sampled in any way.
Not Sampling: The Sampling option supports simple random sampling or stratified random sampling. This is useful if you want to create a smaller representative sample dataset for testing.
Box 2: Partition evenly
Specify the partitioner method: Indicate how you want data to be apportioned to each partition, using these options:
Partition evenly: Use this option to place an equal number of rows in each partition. To specify the number of output partitions, type a whole number in the Specify number of folds to split evenly into text box.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/partition-and-sample
NEW QUESTION: 2
You configure a connection to Microsoft Social Listening but cannot see social insights data in Microsoft Dynamics CRM.
What should you do to make social insights visible in Dynamics CRM?
A. Configure social listening search topics and visuals.
B. In system settings, change the default setting for the Disable Social Engagement option.
C. Ensure that each of your social listening search topics are assigned a category.
D. Select the Reset Social Insights option to refresh the social insights data.
Answer: A
Explanation:
Ref:http://technet.microsoft.com/en-us/library/dn659847(v=crm.6).aspx
NEW QUESTION: 3
머신 러닝 전문가가 이미지 분류 딥 러닝 모델을 구축했습니다. 그러나 Specialist는 교육 및 테스트 정확도가 각각 99 % 및 75 % 인 과적 합 문제에 직면했습니다.
전문가는이 문제를 어떻게 해결해야 하며 그 이유는 무엇입니까?
A. 모델이 충분히 복잡하지 않기 때문에 평탄화 레이어 옆에 있는 조밀 한 레이어의 차원 성을 높여야 합니다.
B. 글로벌 최소값에 도달하기 전에 최적화 프로세스가 종료 되었으므로 epoch 번호를 늘려야 합니다.
C. 모델이 충분히 일반화되지 않았기 때문에 평탄화 레이어에서 드롭 아웃 비율을 높여야합니다.
D. 최적화 프로세스가 로컬 최소값에 갇 혔기 때문에 학습률을 높여야 합니다.
Answer: C
Explanation:
https://kharshit.github.io/blog/2018/05/04/dropout-prevent-overfitting
NEW QUESTION: 4
Performance reporting is important in a program and usually, the portfolio manager aggregates performance information from the portfolio components in order to present the related reports. Which of the following measures can be used in performance reporting?
A. All the options
B. Earned Value
C. Cost Sunk
D. CPI and SPI
Answer: A