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"Samples for X-Prediction?"
Hello,
I'm quite new to Rapidminer, so I still struggle with some details, i.e. for X-Prediction. Especially in the german manual, it starts to describe a very useful example, where a lable/target variable is known for some records and shall be predicted for the rest.
Unformatunately the description of this scenario is interrupted before any detail, i.e. which operator etc.
I think that X-Prediction is the right one, but didn't find any samples how to implement it. At least I guess that the training and test part of a X-Prediction needs to be filled with some blocks/operators by ths user?
I would think that the scenario to predict a feature for records, based on a given subset is used quite often. So can someone point me to some samples or some web sites with information that can guide me further?
Thanks in advance,
Matthias
I'm quite new to Rapidminer, so I still struggle with some details, i.e. for X-Prediction. Especially in the german manual, it starts to describe a very useful example, where a lable/target variable is known for some records and shall be predicted for the rest.
Unformatunately the description of this scenario is interrupted before any detail, i.e. which operator etc.
I think that X-Prediction is the right one, but didn't find any samples how to implement it. At least I guess that the training and test part of a X-Prediction needs to be filled with some blocks/operators by ths user?
I would think that the scenario to predict a feature for records, based on a given subset is used quite often. So can someone point me to some samples or some web sites with information that can guide me further?
Thanks in advance,
Matthias
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Answers
In your position I'd check out the videos on the main website http://rapid-i.com/content/view/189/198/, and then work through the examples in Help->Tutorials ( which cover XVal ).
Finally I need to predict records, based on records I measured before. Is there a better way?
Beside as my background isn't statistics, but telecoms industry, are there some pointer to material to improve my background knowledge?
Thanks,
Matthias
the X-Prediction won't help if you want to make predictions on unlabeled data. To that end, you only need an "Apply Model" operator. We offer a varienty of training courses at http://rapid-i.com/component/option,com_virtuemart/Itemid,180/lang,de/vmcchk,1/.
Best,
Simon
What I still do not fully understand: In case that I have a numer of records, where only few have a label already, what model fits best, as most I tried cannot work with missing values (what would be the label of those unlabled records? If I set the record to somewhat using "Replace Missing Values" wouldn't it change the result of the model?
(As far as I understood the mechanism, the i.e. SVM takes the attributes and tries to find a formula that leads to the given label with the best result. If that is true, giving a random/average value for label to avoid missing values, would change the formula, doesn't it?)
br Matthias
having missing values is different from having missing labels. Missing regular values can easily be replaced, but replacing a missing label does not make a lot of sense. Probably you want to filter them out.
Sorry for recommending things that cost money, but I don't believe this forum is the right place to search for the answers you need at this point of time. The questions you are asking require some understanding of and experience in data mining and cannot be answered by a single post, Your question in parentheses confirms this assumption.
Just so you don't get the impression I am trying to withhold the answer to your question: The answer is "Yes", but that is already all I can say without knowing more about your problem and the data, so it is probably of zero use for you.
Best,
Simon
As I surely miss some of the statistics background, are there some helper what model to use for what scenario, or it is more like "You have to know it yourself?"
Thanks for time,
Matthias
Best,
Simon