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NEW QUESTION: 1
데이터베이스 관리 시스템과 관련된 다음 설명 중 올바르지 않은 것은 무엇입니까?
A. 데이터베이스 관리 시스템은 애플리케이션 소프트웨어와 운영 체제 사이의 계층 역할을 합니다.
B. 데이터베이스 관리 시스템 내의 데이터는 데이터베이스 관리 시스템 관리자만 직접 조작 할 수 있습니다.
C. 데이터베이스 관리 시스템은 운영 체제 자체가 파일에서 수행하는 것이 아니라 테이블 내에서 데이터 조작을 처리합니다.
D. 애플리케이션은 데이터 조작을 위한 명령을 전달한 다음 데이터베이스 관리 시스템에서 실행합니다.
Answer: B
NEW QUESTION: 2
The structure of an organization generally follows its overall strategy. At one end are loosely structured, organic organizations. At the other end are highly centralized, tightly controlled, mechanistic organizations. Consider the overall strategy of a company that is a pioneer in the combination of laser and robotic technologies. The company's scientists and engineers hold many patents. They are continually looking for ways to improve their products as well as to introduce new ones. Identify the most appropriate structural option for this organization.
A. Organic.
B. Mechanistic.
C. Imitative.
D. Bureaucratic.
Answer: A
Explanation:
Organizational structure depends on the company's overall strategy. This organization has adopted an innovation strategy. It introduces major new products or services. The structure that provides the flexibility required for major innovation is organic, a form of organization characterized by a loose structure, low division of labor, low formalization, and decentralization.
NEW QUESTION: 3
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