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I included a Breakpoint in my solution right after the Collect Operator. It is depicted with a red square symbol.
A Breakpoint pauses the Process and shows the intermediate result.
You have three options:
it only appears first example set when joined. Here is my model that i've combined with your xml code. Is there any mistake in my configuration?
The Process itself is correct.
The reason for your problem is that each role (as well as attribute name) can only occur once in each exampleset. Therefore the prediction is always overwritten.
Thus you need to change the role for each attribute. In case all attributes have different names you can use a similar solution as depicted in the screenshot below.
one thing that make me curious, in my model that i build, all example set run same neural network model. The thing is every example set have their unique neural network model, right? can i run neural network model with different neuron size, training cycle, learning rate, momentum to each example set? how to do?
You may have a look into the Operator Optimize Parameters (Grid).
Within the Operator Help there is a Tutorial process linked which should point you in the right direction.
yeah i've tried it and i found the best ANN model for each example set but how to apllied it for each example set? if i put it on neural network operator, it only for one Neural Network Model but it means that this one model is applied to all example set right?
i tried the posted solution.
I found that i like it with a union operator instead of teh join. witht he join it would either repeat the column header modified by source it came from or only have one instance of attribute value.
@binsetyawan Since you are doing everything within Loop Attributes, each Attribute has its own model. Does that answer your question?
@mskinner I suppose that depends on your use case. Did you just replace the Join with the Union Operator? Since Union simply appends your ExampleSets, the number of examples in the final ExampleSet can drastically increase.