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    <!-- 
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    <AnnotationProperty rdf:about="http://purl.obolibrary.org/obo/IAO_0000119"/>
    <AnnotationProperty rdf:about="http://purl.obolibrary.org/obo/IAO_0000115"/>
    


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    <!-- http://purl.obolibrary.org/obo/OBI_0200000 -->

    <Class rdf:about="http://purl.obolibrary.org/obo/OBI_0200000">
        <rdfs:label xml:lang="en">data transformation</rdfs:label>
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    <!-- http://www.ebi.ac.uk/swo/objective/SWO_7000008 -->

    <Class rdf:about="http://www.ebi.ac.uk/swo/objective/SWO_7000008">
        <rdfs:label>class prediction</rdfs:label>
        <rdfs:subClassOf rdf:resource="http://purl.obolibrary.org/obo/OBI_0200000"/>
        <ns2:IAO_0000119>PERSON: James Malone</ns2:IAO_0000119>
        <ns2:IAO_0000119>PERSON: Elisabetta Manduchi</ns2:IAO_0000119>
        <ns2:IAO_0000115>A class prediction objective (sometimes called supervised classification) is a data transformation objective where the aim is to create a predictor from training data through a machine learning technique. The training data consist of pairs of objects (typically vectors of attributes) and class labels for these objects. The resulting predictor can be used to attach class labels to any valid novel input object. Depending on usage, the prediction can be definite or probabilistic. A classification is learned from the training data and can then be tested on test data.</ns2:IAO_0000115>
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