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In general, users pay great attention to product performance.
NEW QUESTION: 1
A. Option D
B. Option A
C. Option B
D. Option E
E. Option C
Answer: A
NEW QUESTION: 2
You are creating a binary classification by using a two-class logistic regression model.
You need to evaluate the model results for imbalance.
Which evaluation metric should you use?
A. Mean Absolute Error
B. Relative Absolute Error
C. Relative Squared Error
D. AUC Curve
Answer: D
Explanation:
Explanation
One can inspect the true positive rate vs. the false positive rate in the Receiver Operating Characteristic (ROC) curve and the corresponding Area Under the Curve (AUC) value. The closer this curve is to the upper left corner, the better the classifier's performance is (that is maximizing the true positive rate while minimizing the false positive rate). Curves that are close to the diagonal of the plot, result from classifiers that tend to make predictions that are close to random guessing.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance#evaluating-a-binar
NEW QUESTION: 3
Which operation is supported by the development mode in Eclipse Tools for Bluemix in IBM Bluemix PaaS?
A. send emails to developer when bug is hit or crash occurs on the application instance
B. scale the application while load testing for development purposes
C. help develop the application by lockingthe access to the application and allowing a fix while nobody else can use it
D. initiate remote debug sessions with that application instance
Answer: D
Explanation:
Reference:https://www304.ibm.com/partnerworld/wps/servlet/download/DownloadServlet?id=7do7u9UN5SciPCA$cnt&at tachmentName=Study_Guide_C5020_285.pdf&token=MTQ1MzQwMDAwNDE0Mg==&locale=en_ ALL_ZZ(page 12)