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NEW QUESTION: 1
You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).
The remaining 1,000 rows represent class 1 (10 percent).
The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.
You need to configure the module.
Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: 300
You type 300 (%), the module triples the percentage of minority cases (3000) compared to the original dataset (1000).
Box 2: 5
We should use 5 data rows.
Use the Number of nearest neighbors option to determine the size of the feature space that the SMOTE algorithm uses when in building new cases. A nearest neighbor is a row of data (a case) that is very similar to some target case. The distance between any two cases is measured by combining the weighted vectors of all features.
By increasing the number of nearest neighbors, you get features from more cases.
By keeping the number of nearest neighbors low, you use features that are more like those in the original sample.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote

NEW QUESTION: 2
What is the PPMP label used for?
A. for the partitioned mVPN model with PIM signaling in an overlay model
B. for all the default MDT and mVPN models
C. for the ingress replication model with BIDIR-PIM in an overlay model
D. only for unicast over MPLS VPN
E. only for the inter-AS mVPN models that use mLDP
Answer: D
Explanation:
Explanation/Reference:
http://lostintransit.se/tag/bgp/
https://tools.ietf.org/html/draft-rosen-l3vpn-mvpn-mspmsi-08#section-3.2.2.1

NEW QUESTION: 3
Solutions Architect는 수신 청구 보고서를 위한 스토리지 솔루션을 CSV 형식으로 설계해야합니다. 데이터는 자주 스캔 할 필요가 없으며 30 일 후에 삭제됩니다.
이러한 요구 사항을 충족하는데 가장 효과적인 서비스는 무엇입니까?
A. Amazon Redshift 클러스터로 로그 가져 오기
B. 로그를 RDS MySQL 인스턴스로 가져옵니다.
C. AWS Data Pipeline을 사용하여 로그를 DynamoDB 테이블로 가져옵니다.
D. 파일을 S3 버킷에 쓰고 Amazon Athena를 사용하여 데이터를 쿼리합니다.
Answer: D

NEW QUESTION: 4
Mark the valid name for a 'text field' in screen painter?
A. _mytext
B. !mytext
C. ?mytext
Answer: B