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model
<?xml version="1.0" ?>
<frame ID="6" name="model">
	<definition>This frame represents ML models, identifiees ML Algorithm that produce the models, and model's Characteristics.</definition>
	<fes>
		<fe ID="1" coretype="True" name="Model">
			<definition>The ML Model is a structure with corresponding interpretation that is produced by induction algorithms as a data generalization serving for description or prediction purposes.</definition>
			<semtypes>
				<semtype>mop:DM-Model</semtype>
			</semtypes>
		</fe>
		<fe ID="2" coretype="False" name="ML Algorithm">
			<definition>This FE identifies an ML Algorithm that produces the Model. </definition>
			<semtypes/>
		</fe>
		<fe ID="3" coretype="False" name="Characteristic">
			<definition>This FE identifies the Characteristic of the Model. </definition>
			<semtypes>
				<semtype>dmop:HypthesisCharacteristic</semtype>
			</semtypes>
		</fe>
	</fes>
	<lexunits>
		<lexunit ID="1" name="model" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="2" name="hypothesis" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="3" name="models" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="4" name="hypotheses" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="5" name="cluster" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="6" name="clustering" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="7" name="rules" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="8" name="patterns" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="9" name="bayes net" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="10" name="decision tree" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="11" name="graphical model" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="12" name="joint distribution" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="13" name="neural network" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="14" name="generative model" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
		<lexunit ID="15" name="bayesian network" pos="N">
			<definition/>
			<semtypes/>
			<annotation>
				<annotated>0</annotated>
				<total>0</total>
			</annotation>
			<lexeme/>
		</lexunit>
	</lexunits>
</frame>
model.txt · Last modified: 2016/03/11 11:48 by pj