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kjetil b halvorsen ♦
kjetil b halvorsen ♦
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I've been doing a machine learning competition where they use RMSLE (Root Mean Squared Logarithmic Error) to evaluate the performance predicting the sale price of a category of equipment. The problem is I'm not sure how to interpret the success of my final result.

For example if I achieved a RMSLE of $1.052$ could I raise it the the exponential power $e$ and interpret it like rmse? (ie. $e^{1.052}=2.863=RMSE$)?

Could I then say that my predictions were $\pm \$2.863$ on average from the the actual prices? Or is there a better way to interpret the metric? Or can the metric even be interpreted at all with the exception of comparing to the other RMSLEs of other models?

Thanks for all your help!

I've been doing a machine learning competition where they use RMSLE (Root Mean Squared Logarithmic Error) to evaluate the performance predicting the sale price of a category of equipment. The problem is I'm not sure how to interpret the success of my final result.

For example if I achieved a RMSLE of $1.052$ could I raise it the the exponential power $e$ and interpret it like rmse? (ie. $e^{1.052}=2.863=RMSE$)?

Could I then say that my predictions were $\pm \$2.863$ on average from the the actual prices? Or is there a better way to interpret the metric? Or can the metric even be interpreted at all with the exception of comparing to the other RMSLEs of other models?

Thanks for all your help!

I've been doing a machine learning competition where they use RMSLE (Root Mean Squared Logarithmic Error) to evaluate the performance predicting the sale price of a category of equipment. The problem is I'm not sure how to interpret the success of my final result.

For example if I achieved a RMSLE of $1.052$ could I raise it the the exponential power $e$ and interpret it like rmse? (ie. $e^{1.052}=2.863=RMSE$)?

Could I then say that my predictions were $\pm \$2.863$ on average from the the actual prices? Or is there a better way to interpret the metric? Or can the metric even be interpreted at all with the exception of comparing to the other RMSLEs of other models?

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edit approved Apr 20, 2013 at 6:36
sashkello
edit approved Apr 20, 2013 at 6:36
sashkello
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I've been doing a machine learning competition where they use RMSLE (Root Mean Squared Logarithmic Error) to evaluate the performance predicting the sale price of a category of equipment. The problem is ImI'm not sure how to interpret the success of my final result.

For example if I achieved a RMSLE of 1.052$1.052$ could I raise it the the exponential power e$e$ and interpret it like rmse? (ie. e^(1.052)=2.863=RMSE $e^{1.052}=2.863=RMSE$)?

Could iI then say that my predictions were +/- $2.863$\pm \$2.863$ on average from the the actual prices? Or is there a better way to interpret the metric? Or can the metric even be interpreted at all with the exception of comparing to the other RMSLEs of other models?

thanksThanks for all your help!

I've been doing a machine learning competition where they use RMSLE (Root Mean Squared Logarithmic Error) to evaluate the performance predicting the sale price of a category of equipment. The problem is Im not sure how to interpret the success of my final result.

For example if I achieved a RMSLE of 1.052 could I raise it the the exponential power e and interpret it like rmse? (ie. e^(1.052)=2.863=RMSE)?

Could i then say that my predictions were +/- $2.863 on average from the the actual prices? Or is there a better way to interpret the metric? Or can the metric even be interpreted at all with the exception of comparing to the other RMSLEs of other models?

thanks for all your help!

I've been doing a machine learning competition where they use RMSLE (Root Mean Squared Logarithmic Error) to evaluate the performance predicting the sale price of a category of equipment. The problem is I'm not sure how to interpret the success of my final result.

For example if I achieved a RMSLE of $1.052$ could I raise it the the exponential power $e$ and interpret it like rmse? (ie. $e^{1.052}=2.863=RMSE$)?

Could I then say that my predictions were $\pm \$2.863$ on average from the the actual prices? Or is there a better way to interpret the metric? Or can the metric even be interpreted at all with the exception of comparing to the other RMSLEs of other models?

Thanks for all your help!

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Opus
Opus
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How do you Interpret RMSLE (Root Mean Squared Logarithmic Error)?

I've been doing a machine learning competition where they use RMSLE (Root Mean Squared Logarithmic Error) to evaluate the performance predicting the sale price of a category of equipment. The problem is Im not sure how to interpret the success of my final result.

For example if I achieved a RMSLE of 1.052 could I raise it the the exponential power e and interpret it like rmse? (ie. e^(1.052)=2.863=RMSE)?

Could i then say that my predictions were +/- $2.863 on average from the the actual prices? Or is there a better way to interpret the metric? Or can the metric even be interpreted at all with the exception of comparing to the other RMSLEs of other models?

thanks for all your help!