Home » Microsoft » DP-100 v.2 » Which of the following is an algorithm that reduces the variances between actual and predicted values?
You make use of Azure Machine Learning Studio to develop a linear regression model. You perform an experiment to assess various algorithms.
Which of the following is an algorithm that reduces the variances between actual and predicted values?
A. Fast Forest Quantile Regression
B. Poisson Regression
C. Boosted Decision Tree Regression
D. Linear Regression
Correct Answer: C
Explanation/Reference:
Mean absolute error (MAE) measures how close the predictions are to the actual outcomes; thus, a lower score is better.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/boosted-decision-tree-regression 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
