source: src/test/java/weka/classifiers/pmml/data/IRIS_MLP.xml @ 10

<?xml version="1.0" encoding="UTF-8"?>
<PMML version="3.0" xmlns="http://www.dmg.org/PMML-3_0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<Header copyright="Copyright (c) Integral Solutions Ltd., 1994 - 2005. All rights reserved.">
<Application name="Clementine" version="10.0"/>
<Annotation>Exported with PMML extensions for use with SPSS SmartScore</Annotation>
</Header>
<DataDictionary numberOfFields="6">
<DataField name="petal_length" optype="continuous" dataType="double">
<Extension name="storageType" value="numeric"/>
<Extension name="measure" value="range"/>
</DataField>
<DataField name="petal_width" optype="continuous" dataType="double">
<Extension name="storageType" value="numeric"/>
<Extension name="measure" value="range"/>
</DataField>
<DataField name="sepal_length" optype="continuous" dataType="double">
<Extension name="storageType" value="numeric"/>
<Extension name="measure" value="range"/>
</DataField>
<DataField name="sepal_width" optype="continuous" dataType="double">
<Extension name="storageType" value="numeric"/>
<Extension name="measure" value="range"/>
</DataField>
<DataField name="class" optype="categorical" dataType="string">
<Extension name="storageType" value="string"/>
<Extension name="measure" value="set"/>
<Value value="Iris-setosa" property="valid"/>
<Value value="Iris-versicolor" property="valid"/>
<Value value="Iris-virginica" property="valid"/>
</DataField>
<DataField name="$NC-SPECIES" optype="continuous" dataType="double">
<Extension name="storageType" value="numeric"/>
<Extension name="measure" value="range"/>
</DataField>
</DataDictionary>
<NeuralNetwork modelName="IRIS_MLP" functionName="classification" algorithmName="Neural Net" activationFunction="logistic">
<Extension name="normalizationMethod" value="limitedDifference"/>
<MiningSchema>
<MiningField name="petal_length" usageType="active" missingValueReplacement="3.95" missingValueTreatment="asMedian" outliers="asExtremeValues" lowValue="1.0" highValue="6.9"/>
<MiningField name="petal_width" usageType="active" missingValueReplacement="1.3" missingValueTreatment="asMedian" outliers="asExtremeValues" lowValue="0.1" highValue="2.5"/>
<MiningField name="sepal_length" usageType="active" missingValueReplacement="6.1" missingValueTreatment="asMedian" outliers="asExtremeValues" lowValue="4.3" highValue="7.9"/>
<MiningField name="sepal_width" usageType="active" missingValueReplacement="3.2" missingValueTreatment="asMedian" outliers="asExtremeValues" lowValue="2.0" highValue="4.4"/>
<MiningField name="class" usageType="predicted"/>
<MiningField name="$NC-SPECIES" usageType="supplementary"/>
</MiningSchema>
<NeuralInputs>
<NeuralInput id="0">
<DerivedField optype="continuous" dataType="double">
<NormContinuous field="petal_length">
<LinearNorm orig="1" norm="0"/>
<LinearNorm orig="6.9" norm="1"/>
</NormContinuous>
</DerivedField>
</NeuralInput>
<NeuralInput id="1">
<DerivedField optype="continuous" dataType="double">
<NormContinuous field="petal_width">
<LinearNorm orig="0.1" norm="0"/>
<LinearNorm orig="2.5" norm="1"/>
</NormContinuous>
</DerivedField>
</NeuralInput>
<NeuralInput id="2">
<DerivedField optype="continuous" dataType="double">
<NormContinuous field="sepal_length">
<LinearNorm orig="4.3" norm="0"/>
<LinearNorm orig="7.9" norm="1"/>
</NormContinuous>
</DerivedField>
</NeuralInput>
<NeuralInput id="3">
<DerivedField optype="continuous" dataType="double">
<NormContinuous field="sepal_width">
<LinearNorm orig="2" norm="0"/>
<LinearNorm orig="4.4" norm="1"/>
</NormContinuous>
</DerivedField>
</NeuralInput>
</NeuralInputs>
<NeuralLayer>
<Neuron id="4" bias="2.03473228253">
<Con from="0" weight="-4.0256456408"/>
<Con from="1" weight="-3.83730095974"/>
<Con from="2" weight="0.0624800821416"/>
<Con from="3" weight="2.40206472093"/>
</Neuron>
<Neuron id="5" bias="1.6526137028">
<Con from="0" weight="-5.01759484187"/>
<Con from="1" weight="-5.23173402014"/>
<Con from="2" weight="-1.80228751097"/>
<Con from="3" weight="2.98662625446"/>
</Neuron>
<Neuron id="6" bias="-11.6218815784">
<Con from="0" weight="11.3795015654"/>
<Con from="1" weight="9.67298427591"/>
<Con from="2" weight="-2.10906925011"/>
<Con from="3" weight="-3.58414535245"/>
</Neuron>
</NeuralLayer>
<NeuralLayer>
<Neuron id="7" bias="-4.54626929708">
<Con from="4" weight="4.36547390082"/>
<Con from="5" weight="4.69477556292"/>
<Con from="6" weight="-4.37727158969"/>
</Neuron>
<Neuron id="8" bias="4.85147554911">
<Con from="4" weight="-2.51631420956"/>
<Con from="5" weight="-6.71322276698"/>
<Con from="6" weight="-9.34181840082"/>
</Neuron>
<Neuron id="9" bias="-2.95716683639">
<Con from="4" weight="-6.98136941982"/>
<Con from="5" weight="-4.64823127158"/>
<Con from="6" weight="7.63041165053"/>
</Neuron>
</NeuralLayer>
<NeuralOutputs>
<NeuralOutput outputNeuron="7">
<DerivedField optype="categorical" dataType="string">
<NormDiscrete field="class" value="Iris-setosa"/>
</DerivedField>
</NeuralOutput>
<NeuralOutput outputNeuron="8">
<DerivedField optype="categorical" dataType="string">
<NormDiscrete field="class" value="Iris-versicolor"/>
</DerivedField>
</NeuralOutput>
<NeuralOutput outputNeuron="9">
<DerivedField optype="categorical" dataType="string">
<NormDiscrete field="class" value="Iris-virginica"/>
</DerivedField>
</NeuralOutput>
</NeuralOutputs>
</NeuralNetwork>
</PMML>