Need guidance for Modeling and Preparation Datasets is given
Dear Community,
just started to get confi with rapidminer (absolute beginner)
I´ve tried to build a process mainly focused on labeling target attribute, detecting outliers, missing values.
In the end I should be able to build a model which can predict wine quality
therefore I need to build a baseline classification with training and test data
The modell should be improved in the end and evaluated
I am really stuck in the preparation process.
For further details please have a look at my processes and lecture sheet.
I would be greatefull for any hint or guidance
Best regards
Atilla
just started to get confi with rapidminer (absolute beginner)
I´ve tried to build a process mainly focused on labeling target attribute, detecting outliers, missing values.
In the end I should be able to build a model which can predict wine quality
therefore I need to build a baseline classification with training and test data
The modell should be improved in the end and evaluated
I am really stuck in the preparation process.
For further details please have a look at my processes and lecture sheet.
I would be greatefull for any hint or guidance
Best regards
Atilla
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Hi @Atilla
I review your process. there are some redundant operators but in general good work. I don't know where are you stuck. you removed the noise, missing values and reduced the label to three values.
Best
Hi @Atilla,
Without the excel file I can't run the process. however, looking at process I can see that you are using a Select Attributes operator and you are selecting all of them, It's no necessary. also you are using a Set Role Operator, after Select Attributes, with the label attribute but assigning it a regular role, for then assigning it a label label role into the Cross Validation Operator. you can remove the first Set Role Operator
Best
Without the excel file I can't run the process. however, looking at process I can see that you are using a Select Attributes operator and you are selecting all of them, It's no necessary. also you are using a Set Role Operator, after Select Attributes, with the label attribute but assigning it a regular role, for then assigning it a label label role into the Cross Validation Operator. you can remove the first Set Role Operator
Best
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Hi @Atilla
I review your process. there are some redundant operators but in general good work. I don't know where are you stuck. you removed the noise, missing values and reduced the label to three values.
Best
Thank´s for your review I apprecite it. Now I finished it with modelling and testing. Would you keen to have a look on that process? Are they mistakes or redundancies?
Kindley Regards
Kindley Regards
Hi @Atilla,
Without the excel file I can't run the process. however, looking at process I can see that you are using a Select Attributes operator and you are selecting all of them, It's no necessary. also you are using a Set Role Operator, after Select Attributes, with the label attribute but assigning it a regular role, for then assigning it a label label role into the Cross Validation Operator. you can remove the first Set Role Operator
Best
Without the excel file I can't run the process. however, looking at process I can see that you are using a Select Attributes operator and you are selecting all of them, It's no necessary. also you are using a Set Role Operator, after Select Attributes, with the label attribute but assigning it a regular role, for then assigning it a label label role into the Cross Validation Operator. you can remove the first Set Role Operator
Best