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How do I create these layers (image) with stacking?
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@Jack530 wants to know the answer to this question.
"Hi. My goal is to create a highly accurate linear regression model. Such as the image in the link displays (logistic regression in the image). My question is how, probably with the stacking operator, do i create these layers? I now start with read cvs (training set with al corresponding roles/labels), then how do you move to a the model in the picture and eventually a highly accurate model (being aware of cross-validation/optimising parameters and all other important operators).
These are the steps that should be taken according to the image, and am stuck on how to implement in RapidMiner:
1. A diverse set of models with an assembled result
2. Subsequently the output of 1. is the input this phase; assembling models (bagging?)
3. Lastly the output of 2. is the input of the eventual model (so built on the predictions of al preliminary models).
I would greatly appreciate advice."
"Hi. My goal is to create a highly accurate linear regression model. Such as the image in the link displays (logistic regression in the image). My question is how, probably with the stacking operator, do i create these layers? I now start with read cvs (training set with al corresponding roles/labels), then how do you move to a the model in the picture and eventually a highly accurate model (being aware of cross-validation/optimising parameters and all other important operators).
These are the steps that should be taken according to the image, and am stuck on how to implement in RapidMiner:
1. A diverse set of models with an assembled result
2. Subsequently the output of 1. is the input this phase; assembling models (bagging?)
3. Lastly the output of 2. is the input of the eventual model (so built on the predictions of al preliminary models).
I would greatly appreciate advice."
![Image: https://us.v-cdn.net/6030995/uploads/editor/21/krfmbq75kbih.png](https://us.v-cdn.net/6030995/uploads/editor/21/krfmbq75kbih.png)
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This is all completely do-able in RapidMiner, albeit very tedious. Is there a definite need to replicate this same structure? You say you want to create a "highly accurate" model but there is no guarantee that the final model in this architecture is significantly more accurate than a single LR model---that totally depends on the data.
I would suggest you start by building a single LR model and assessing its performance against some other popular ML algorithms like k-nn or GBT. This is easy to do with AutoModel. You might then consider a simpler ensemble solution using a Voting or Stacking operator. But there seems like no need to go directly to the layout depicted in this diagram.
Lindon Ventures
Data Science Consulting from Certified RapidMiner Experts
First of all, there is absolutely no need to replicate the structure of the image. It was attached just to display a structure that could define the best algorithm. (The picture that was attached to the initial post was an extremely complex version, I may be looking for a way more general one)
However, allow me to explain my mission. I want to build the best possible predictive algorithm for predicting house prices.
First I indeed looked at what models perform best. I attached the results of this run down below in a typed column.
My goal is that I want to combine/structure (some of the) models to lower our eventual RMSE.
First question now is, what models would you include (would you include all). Moreover, how would this look in Rapidminer so that the structure through Stacking/Bagging/Voting (what would you recommend and how do I implement this in Rapidminer practically) will lead to the lowest possible RMSE (which is of course dependant on the dataset) on our test dataset. Altogether, how do i connect the models and in what order/structure in Rapidminer (by means of trial and error of course - what combination produces lower RMSEs than others) so that I can work to the lowest possible RMSE?
Again I really appreciate your time and effort in answering this question. I know it is a pretty in depth question and therefore thanks a lot.
Regards,
RMSE:
Lindon Ventures
Data Science Consulting from Certified RapidMiner Experts