Automatically apply learned classifier

Legacy User

Hi,

I've generated a classifier based on the learner decision trees and would
like to use this learned model for future examples to predict their classes.

How can this be accomplished? My future examples are generated by
another application that writes them into a CSV file which was also
used as IO module during the learning phase. Now, I'm wondering how
this new example can be passed to RapidMiner which automatically
applies the learned model on that example and somehow outputs the
predicted class which I could further use in another application.

Generating the example, invoking RapidMiner's JAR file and reading
the predicted class from a file should be not a problem. But I don't
know how to apply the model to the read example and how to dump
the predicted class.

Any ideas?

Regards,
Martin

steffen

Hello

I am afraid I got you wrong...

Generating the example, invoking RapidMiner's JAR file and reading the predicted class from a file should be not a problem. But I don't know how to apply the model to the read example and how to dump the predicted class.

Run a process like this one (e.g. using rapidminer without gui):

<operator name="Root" class="Process" expanded="yes">
    <operator name="read_new_data" class="SimpleExampleSource">
    </operator>
    <operator name="load_model" class="ModelLoader">
    </operator>
    <operator name="apply_model" class="ModelApplier">
        <list key="application_parameters">
        </list>
    </operator>
    <operator name="skip_everything_but_id_prediction" class="FeatureNameFilter">
        <parameter key="except_features_with_name"	value="id||prediction.*"/>
        <parameter key="filter_special_features"	value="true"/>
        <parameter key="skip_features_with_name"	value=".*"/>
    </operator>
    <operator name="write_results" class="CSVExampleSetWriter">
    </operator>
</operator>

...assuming that you have saved the created model before...

hope this was helpful,

Steffen