- (Topic 2)
What are two metrics that you can use to evaluate a regression model? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Correct Answer:
AC
A: R-squared (R2), or Coefficient of determination represents the predictive power of the model as a value between -inf and 1.00. 1.00 means there is a perfect fit, and the fit can be arbitrarily poor so the scores can be negative.
C: RMS-loss or Root Mean Squared Error (RMSE) (also called Root Mean Square Deviation, RMSD), measures the difference between values predicted by a model and the values observed from the environment that is being modeled.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/metrics
- (Topic 5)
You need to develop a chatbot for a website. The chatbot must answer users questions based on the information m the following documents
• A product troubleshooting guide m a Microsoft Word document
• A frequently asked questions (FAQ) list on a webpage Which service should you use to process the documents?
Correct Answer:
D
- (Topic 5)
During the process of Machine Learning, when should you review evaluation metrics?
Correct Answer:
D
HOTSPOT - (Topic 2)
To complete the sentence, select the appropriate option in the answer area.
Solution:
Regression is a machine learning task that is used to predict the value of the label from a set of related features.
Does this meet the goal?
Correct Answer:
A
DRAG DROP - (Topic 5)
You plan to deploy an Azure Machine Learning model by using the Machine Learning designer
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Solution:
Does this meet the goal?
Correct Answer:
A