Skip to main content

Questions tagged [r-squared]

For questions regarding R-squared ($R^2$), a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable or variables in a regression model.

1 vote
1 answer
73 views

Most discussions on model prediction says that you should focus on error metrics, like RMSE, MSE, MAE or MAPE. Some even argue that r-squared can be low in a good model. However, I can't think of a ...
Andrew Joplh's user avatar
0 votes
0 answers
158 views

In my models, R2 in training and test sets are close to each other, but in RMSE, MSE, MAE of some models, these are very different? what is the reason Is there a solution?
Erfan Mollai's user avatar
1 vote
1 answer
773 views

I'm trying to predict some variables for MOF's (from a scientific paper) using the Random Forest model in Phyton, but the value of R2 is negative (different from the paper, which was positive). I ...
Vinicius Maia's user avatar
0 votes
0 answers
102 views

We can compute real or population correlation(rho) by square-root of 1 minus R-squared.Is this a correct interpretation? Does population correlation mean a real correlation measured as square-root of ...
Subhash C. Davar's user avatar
2 votes
1 answer
98 views

I was running a Linear Regression with Wooldridge dataset named GPA2, which is found on Python library named wooldridge. I tried two linear regressions. The first: ...
dsbr__0's user avatar
  • 191
0 votes
0 answers
73 views

I was reading the paper "Consistent Individualized Feature Attribution for Tree Ensembles" by Scott Lundberg et al. and cannot understand how the calculation for the $R^2$ works here - see ...
Penguines's user avatar
0 votes
1 answer
39 views

I am solving a Multiple Linear Regression problem and judging the model by looking at R-square and Adjusted R-square metrics. In recent iteration which are yielding desired coefficients directionally ...
Prasad Patil's user avatar
3 votes
0 answers
309 views

I have a high-dimensional space, say $\mathbb{R}^{1000}$, and I have samples $y_1, \ldots , y_n \in \mathbb{R}^{1000}$ and $\hat{y}_1, \ldots , \hat{y}_n \in \mathbb{R}^{1000}$. Would $$ R^2 = 1 - \...
AspiringToAspire's user avatar
1 vote
1 answer
3k views

If for example I have the value of RMSE can I calculate the $R^2$? And vice versa if I have the value of $R^2$ can I calculate the value of RMSE? I have all predictions, dataset, training set, and ...
Djakarta_zero's user avatar
0 votes
1 answer
29 views

I'm trying to build model for this datatset (Age prediction): The input image has the shape: 3, 128, 128 and the predicted labels (ages) range between 20 to 51. I ...
user3668129's user avatar
1 vote
1 answer
266 views

I am training an XGBoost model, xgbr, using xgb.XGBRegressor() with 13 features and one numeric target. The R2 on the test set ...
volkan g's user avatar
  • 121
2 votes
2 answers
1k views

I'm trying to create a linear regression model with use of PolynomialFeatures. But when I evaluate it, I get really strange scores. I know that R^2 can be applied to this model and I think I've trying ...
kosekk_g's user avatar
1 vote
0 answers
55 views

Does the appliance of R-squared to non-linear models depends on how we calculate it? $R^2 = \frac{SS_{exp}}{SS_{tot}}$ is going to be an inadequate measure for non-linear models since an increase of $...
mathgeek's user avatar
  • 121
1 vote
3 answers
144 views

I am trying to determine which model result is better. Both results are trying to achieve the same objective, the only difference is the exact data that is being used. I used ...
justanewb's user avatar

15 30 50 per page