In E-Miner, I see 2 selections in the Model Comparison node:
- Average Squared Error
- Mean Squared Error
What is the difference?
Searching the HELP does not yield any decent description:
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The Selection Statistic choices are as follows:
Default — The default selection uses different statistics based on the type of target variable and whether a profit/loss matrix has been defined.
If a profit/loss matrix is defined for a categorical target, the average profit or average loss is used.
If no profit/loss matrix is defined for a categorical target, the misclassification rate is used.
If the target variable is interval, the average squared error is used.
Akaike's Information Criterion — chooses the model with the smallest Akaike's Information Criterion value.
Average Squared Error — chooses the model with the smallest average squared error value.
Mean Squared Error — chooses the model with the smallest mean squared error value.
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Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.
Find more tutorials on the SAS Users YouTube channel.