Extract regression equation
Hi,
I'm building a model to predict a numeric continuous variable by using another numeric variable.
Logarithmic or polynomial equations better fit my data. They have given a lower error rate than linear regression, but I'm unsure how to extract the model equation (formula) from the model I built.
Here is the algorithm I used:
- Generalized Linear Model
- family: gaussian
- link: log
(Green label = prediction)
Also, I am trying to use polynomial regression for my model since it shows the equation in the model output. However, the prediction is totally off, not sure if I made any mistake in the setting. (Green label = prediction)
Thanks,
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Hi ceaperez,
Thank you for the reference.
I understand the GLM formula and interpretation. However, I'm not sure where to find the model equation I built which I am planning to apply the model into other application (by using the formula) to predict new testing data (e.g., label = a + b(x) + c (x) or label = a+b log (x)
. Also, I am wondering if the rapidminer GLM could automatically generate interaction terms when I have 2 or more numeric or binomial independent variables?
Thanks,
Thank you for the reference.
I understand the GLM formula and interpretation. However, I'm not sure where to find the model equation I built which I am planning to apply the model into other application (by using the formula) to predict new testing data (e.g., label = a + b(x) + c (x) or label = a+b log (x)
. Also, I am wondering if the rapidminer GLM could automatically generate interaction terms when I have 2 or more numeric or binomial independent variables?
Thanks,
Altair Employee
Hi @Louie,
If you click on the data option into the left menu, you can see a table with the attributes and coefficients. You can construct the model with the more significant variables using the p-value and significance level as criteria.
The attached image is from sample process for GLM regression.
Best,
Cesar
If you click on the data option into the left menu, you can see a table with the attributes and coefficients. You can construct the model with the more significant variables using the p-value and significance level as criteria.
The attached image is from sample process for GLM regression.
Best,
Cesar
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Hi @Louie,
If you click on the data option into the left menu, you can see a table with the attributes and coefficients. You can construct the model with the more significant variables using the p-value and significance level as criteria.
The attached image is from sample process for GLM regression.
Best,
Cesar
If you click on the data option into the left menu, you can see a table with the attributes and coefficients. You can construct the model with the more significant variables using the p-value and significance level as criteria.
The attached image is from sample process for GLM regression.
Best,
Cesar
There is a good guide about the use and interpretation of GLM. It was very useful for me.
https://statisticsbyjim.com/regression/interpret-coefficients-p-values-regression/
Best,
Cesar