¡Cuál es el porcentaje de error relativo que me indica que mi modelo es válido?
MiguelHH98
New Altair Community Member
Hola!
Mi modelo incluye aproximadamente 100 datos por cada variable. El error relativo resultante al correr el modelo es de 7.9% bajo el método elegido como "best performance". Quisiera saber si con ese error mi modelo es válido o, si es que no, cuál sería el adecuado.
Espero su pronta respuesta. Gracias.
Saludos,
Miguel Hinostroza
Mi modelo incluye aproximadamente 100 datos por cada variable. El error relativo resultante al correr el modelo es de 7.9% bajo el método elegido como "best performance". Quisiera saber si con ese error mi modelo es válido o, si es que no, cuál sería el adecuado.
Espero su pronta respuesta. Gracias.
Saludos,
Miguel Hinostroza
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Best Answers
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Hello @MiguelHH98
Based on the results, the GBT has better performance than others. So, to define if the model is valid, my choice is to look at correlation values and RMSE. You can take R^2 (squared correlation) as a reference. An R^2 >0.5 is good for many domains. In your case, you can select the option correlation from the drop-down menu (instead of relative error) and calculate the square of correlation to see if you have good R^2 value.
The standard values change based on domains and the amount of error acceptance is also based on domain knowledge.2 -
@MiguelHH98
Hi
Also this is Auto model and in Auto model, RM automatically choose best algorithms for your data and make process for them so all of them are valid but the best one is Gradient Boosted Trees according to your screen shot. You can use other metrics for that in order to evaluate your process.
I hope this helps
mbs1
Answers
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Hello
@MiguelHH98
Please show the result of your process ( with screen shot) to see that and can explain your result.
Regards
mbs1 -
Hi, mbs:
These are the results:
I used, approximately, 20 attributes and 100 values per attribut. I want to know if my model is valid according to the best relative error (Gradient Boosted Trees) or what percentage could you recommend. Thanks.
Regards,
MiguelHH981 -
Hello @MiguelHH98
Based on the results, the GBT has better performance than others. So, to define if the model is valid, my choice is to look at correlation values and RMSE. You can take R^2 (squared correlation) as a reference. An R^2 >0.5 is good for many domains. In your case, you can select the option correlation from the drop-down menu (instead of relative error) and calculate the square of correlation to see if you have good R^2 value.
The standard values change based on domains and the amount of error acceptance is also based on domain knowledge.2 -
@MiguelHH98
Hi
Also this is Auto model and in Auto model, RM automatically choose best algorithms for your data and make process for them so all of them are valid but the best one is Gradient Boosted Trees according to your screen shot. You can use other metrics for that in order to evaluate your process.
I hope this helps
mbs1 -