RMSLE, or the Root Mean Square Logarithmic Error, is the ratio (the log) between the actual values in your data and predicted values in the model. Use RMSLE instead of RMSE if an under-prediction is worse than an over-prediction – where underestimating is more problematic than overestimating. For example, is it worse to forecast too much sales revenue or too little? Use RMSLE when your data has large numbers to predict and you don’t want to penalize large differences between the actual and predicted values (because both of the values are large numbers).
Squark is a Software as a Service (SaaS) platform for no code predictive analytics that makes pragmatic AI predictions simple, with absolutely no coding. Squark goes beyond traditional automated machine learning — AutoML — and gives everyone the freedom to achieve better outcomes with AI power in human control.
67 South Bedford St., Suite 400W
Burlington, MA 01803
+1 (888) 747-8471
Subscribe to Squark News
Receive AI tips, newsletters, and cool email from Squark. Change preferences or unsubscribe any time.