How to Generate Optimum ExampleSet
giannidiorio
New Altair Community Member
Hello to everyone,
I'm quite new in RapidMiner and I had a little problem or better question: How can I generate optimum ExampleSet?
I try to explain myself:
I want to implement an optimization process in RM5.3, basically my objective is to create a process where I have a classification algorithm trained with a set of configurations (i.e. the training data is constituted by a set of attribute each one representing a configuration parameter, the label is simply 1 for good configuration and 0 for bad configuration). Once the algorithm is trained and the model is created my question is: how to start a cycle to find a good exampleSet to feed the ApplyModel operator (i.e. an exampleSet that is able to give 1 when processed)? I have created also a correlation matrix operator in order to identify the attributes of the training data with higher weight, however I'm not able to loop and change this attributes until the result is 1. How can I implement it? I want to create an auto-adaptation process in java, or in other words I have a set of good and bad configurations and I want to start a process which result is a good configuration.
Thank you for the help.
Best Regards,
Giovanni
I'm quite new in RapidMiner and I had a little problem or better question: How can I generate optimum ExampleSet?
I try to explain myself:
I want to implement an optimization process in RM5.3, basically my objective is to create a process where I have a classification algorithm trained with a set of configurations (i.e. the training data is constituted by a set of attribute each one representing a configuration parameter, the label is simply 1 for good configuration and 0 for bad configuration). Once the algorithm is trained and the model is created my question is: how to start a cycle to find a good exampleSet to feed the ApplyModel operator (i.e. an exampleSet that is able to give 1 when processed)? I have created also a correlation matrix operator in order to identify the attributes of the training data with higher weight, however I'm not able to loop and change this attributes until the result is 1. How can I implement it? I want to create an auto-adaptation process in java, or in other words I have a set of good and bad configurations and I want to start a process which result is a good configuration.
Thank you for the help.
Best Regards,
Giovanni
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