Hi every one !

Using sklearn and linear model I made a linear regression and I reached out to a function named "score". Does anyone know what does it exactly calculate?

The code for this function is like this:
model.score(X,Y)

Thanks in advance!

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On Sun, Oct 23, 2022 at 05:11:10AM -0700, Fatemeh Heydari wrote:

model.score(X,Y)

That will basically check how good your model is.

It takes a bunch of X values with known values, which you provide in Y
and compares the output of model.Predict(X) with the Y's and gives you
some metrics as to how good that performed.

In the case of linear regression that be R^2, the coefficient of determination of the prediction.

Cheers,
Reto

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On Monday, October 24, 2022 at 7:14:10 AM UTC-7, Reto wrote:

On Sun, Oct 23, 2022 at 05:11:10AM -0700, Fatemeh Heydari wrote:

model.score(X,Y)

That will basically check how good your model is.

It takes a bunch of X values with known values, which you provide in Y
and compares the output of model.Predict(X) with the Y's and gives you
some metrics as to how good that performed.

In the case of linear regression that be R^2, the coefficient of determination
of the prediction.

Cheers,
Reto

Dear Reto
Thanks for your attention. But I calculated R^2 for the model with the code : r2_score(predictedY,Y)
and I got different result from the "score " function. I wish to know what mathematical formulation is behind this function

Thanks again

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There's a fairly good rundown of score() here:

"[Python/Sklearn] How does .score() works?" https://www.kaggle.com/getting-started/27261

On 10/26/2022 2:18 AM, Fatemeh Heydari wrote:

On Monday, October 24, 2022 at 7:14:10 AM UTC-7, Reto wrote:

On Sun, Oct 23, 2022 at 05:11:10AM -0700, Fatemeh Heydari wrote:

model.score(X,Y)

That will basically check how good your model is.

It takes a bunch of X values with known values, which you provide in Y
and compares the output of model.Predict(X) with the Y's and gives you
some metrics as to how good that performed.

In the case of linear regression that be R^2, the coefficient of determination
of the prediction.

Cheers,
Reto

Dear Reto
Thanks for your attention. But I calculated R^2 for the model with the code : r2_score(predictedY,Y)
and I got different result from the "score " function. I wish to know what mathematical formulation is behind this function

Thanks again

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