/
neural_insurance.pmml
144 lines (144 loc) · 5.33 KB
/
neural_insurance.pmml
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<PMML xmlns="http://www.dmg.org/PMML-4_3" version="4.3">
<Header copyright="DMG.org"/>
<DataDictionary numberOfFields="5">
<DataField name="gender" optype="categorical" dataType="string">
<Value value="female"/>
<Value value="male"/>
</DataField>
<DataField name="no of claims" optype="categorical" dataType="string">
<Value value="0"/>
<Value value="1"/>
<Value value="3"/>
<Value value=">3"/>
<Value value="2"/>
</DataField>
<DataField name="domicile" optype="categorical" dataType="string">
<Value value="suburban"/>
<Value value="urban"/>
<Value value="rural"/>
</DataField>
<DataField name="age of car" optype="continuous" dataType="double"/>
<DataField name="amount of claims" optype="continuous" dataType="double"/>
</DataDictionary>
<NeuralNetwork modelName="Neural Insurance" functionName="regression" activationFunction="logistic" numberOfLayers="2">
<MiningSchema>
<MiningField name="gender"/>
<MiningField name="no of claims"/>
<MiningField name="domicile"/>
<MiningField name="age of car"/>
<MiningField name="amount of claims" usageType="target"/>
</MiningSchema>
<NeuralInputs numberOfInputs="10">
<NeuralInput id="0">
<DerivedField optype="continuous" dataType="double">
<NormContinuous field="age of car">
<LinearNorm orig="0.01" norm="0"/>
<LinearNorm orig="3.07897" norm="0.5"/>
<LinearNorm orig="11.44" norm="1"/>
</NormContinuous>
</DerivedField>
</NeuralInput>
<NeuralInput id="1">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="gender" value="male"/>
</DerivedField>
</NeuralInput>
<NeuralInput id="2">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="no of claims" value="0"/>
</DerivedField>
</NeuralInput>
<NeuralInput id="3">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="no of claims" value="1"/>
</DerivedField>
</NeuralInput>
<NeuralInput id="4">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="no of claims" value="3"/>
</DerivedField>
</NeuralInput>
<NeuralInput id="5">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="no of claims" value=">3"/>
</DerivedField>
</NeuralInput>
<NeuralInput id="6">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="no of claims" value="2"/>
</DerivedField>
</NeuralInput>
<NeuralInput id="7">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="domicile" value="suburban"/>
</DerivedField>
</NeuralInput>
<NeuralInput id="8">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="domicile" value="urban"/>
</DerivedField>
</NeuralInput>
<NeuralInput id="9">
<DerivedField optype="continuous" dataType="double">
<NormDiscrete field="domicile" value="rural"/>
</DerivedField>
</NeuralInput>
</NeuralInputs>
<NeuralLayer numberOfNeurons="3">
<Neuron id="10">
<Con from="0" weight="-2.08148"/>
<Con from="1" weight="3.69657"/>
<Con from="2" weight="-1.89986"/>
<Con from="3" weight="5.61779"/>
<Con from="4" weight="0.427558"/>
<Con from="5" weight="-1.25971"/>
<Con from="6" weight="-6.55549"/>
<Con from="7" weight="-4.62773"/>
<Con from="8" weight="1.97525"/>
<Con from="9" weight="-1.0962"/>
</Neuron>
<Neuron id="11">
<Con from="0" weight="-0.698997"/>
<Con from="1" weight="-3.54943"/>
<Con from="2" weight="-3.29632"/>
<Con from="3" weight="-1.20931"/>
<Con from="4" weight="1.00497"/>
<Con from="5" weight="0.033502"/>
<Con from="6" weight="1.12016"/>
<Con from="7" weight="0.523197"/>
<Con from="8" weight="-2.96135"/>
<Con from="9" weight="-0.398626"/>
</Neuron>
<Neuron id="12">
<Con from="0" weight="0.904057"/>
<Con from="1" weight="1.75084"/>
<Con from="2" weight="2.51658"/>
<Con from="3" weight="-0.151895"/>
<Con from="4" weight="-2.88008"/>
<Con from="5" weight="0.920063"/>
<Con from="6" weight="-3.30742"/>
<Con from="7" weight="-1.72251"/>
<Con from="8" weight="-1.13156"/>
<Con from="9" weight="-0.758563"/>
</Neuron>
</NeuralLayer>
<NeuralLayer numberOfNeurons="1">
<Neuron id="13">
<Con from="10" weight="0.76617"/>
<Con from="11" weight="-1.5065"/>
<Con from="12" weight="0.999797"/>
</Neuron>
</NeuralLayer>
<NeuralOutputs numberOfOutputs="1">
<NeuralOutput outputNeuron="13">
<DerivedField optype="continuous" dataType="double">
<NormContinuous field="amount of claims">
<LinearNorm orig="0" norm="0.1"/>
<LinearNorm orig="1291.68" norm="0.5"/>
<LinearNorm orig="5327.26" norm="0.9"/>
</NormContinuous>
</DerivedField>
</NeuralOutput>
</NeuralOutputs>
</NeuralNetwork>
</PMML>