Hello.

I was wondering what “Adjusted R squared” option in “Numeric Scorer” node is.

Because there is no explain about this option on Knime Hub.

I’d appreciate if someone could tell me what it is.

Thanks,

hhkim

Hello.

I was wondering what “Adjusted R squared” option in “Numeric Scorer” node is.

Because there is no explain about this option on Knime Hub.

I’d appreciate if someone could tell me what it is.

Thanks,

hhkim

Hi @hhkim

I believe the “Adjusted R Squared” is quite well explained with its equation in the following web site:

Hope it helps.

Best

Ael

1 Like

It was helpful to me.

Thank you so much!!

Best Regards,

hhkim

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r-squared refers to the ‘goodness’ of fit for a particular model with no regard for the number of independent variables. Whereas, adjusted r-squared takes into account the number of independent variables.

So if you have a regression equation such as

y = mx + nx1 + ox2 + b

The r-squared will tell you how well that equation describes your data. If you add more independent variables (p, q, r, s …) then the r-square value will improve because you are in essence more specifically defining your sample data. Using adjusted R-squared metric instead takes into account that you have added more independent variables and will ‘penalize’ the result for the more variables you add which don’t fit the sample data. This is a good way to test the variables, either by adding in one at a time and checking when the adj-R2 starts to deteriorate or by starting with all the variables and removing one at a time until the adj-R2 doesn’t improve.

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