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NEW QUESTION: 1
You are working on an Azure Machine Learning experiment that uses four different logistic regression algorithms. You are evaluating the algorithms based on the data in the following table.

Which model produces predictions that are the closest to the actual outcomes?
A. Model 4
B. Model 2
C. Model 3
D. Model 1
Answer: C
Explanation:
Explanation/Reference:
Explanation:
Mean absolute error (MAE) measures how close the predictions are to the actual outcomes; thus, a lower score is better.
Relative absolute error (RAE) is the relative absolute difference between expected and actual values; relative because the mean difference is divided by the arithmetic mean.
Root mean squared error (RMSE) creates a single value that summarizes the error in the model. By squaring the difference, the metric disregards the difference between over-prediction and under-prediction.
References: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate- model

NEW QUESTION: 2
Which two layers of the OSI model are combined in the Internet protocol suite network access layer?
(Choose two.)
A. 0
B. 1
C. 2
D. 3
E. 4
F. 5
G. 6
Answer: C,F
Explanation:
Explanation/Reference:
Explanation:
http://en.wikipedia.org/wiki/Internet_protocol_suite

NEW QUESTION: 3
Which one of the following is not an event-based elicitation technique?
A. Interface analysis
B. Interview
C. Focus group
D. Workshop
Answer: A
Explanation:
Explanation/Reference:
Interface analysis is not an event-based elicitation technique. It is an elicitation technique that identifies interfaces between solutions and how the interfaces will interact.
D is incorrect. A workshop is an event-based elicitation technique.
A is incorrect. A focus group is an event-based elicitation technique.
C is incorrect. An interview is an event-based elicitation technique.