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Make rule induction tests compatible with both python 3.7 and 3.6
Ripper has a subtle behavior change (as if we used a different random seed) between python 3.6 and 3.7 so one of the tests was failing. Do a runtime version check to choose which expected value to use. This can be removed once we stop supporting 3.6. Signed-off-by: Yusik Kim <[email protected]>
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‎tests/rule_induction/trxf/pmml_export/resources/adult_py36.pmml‎

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<?xml version="1.0" encoding="UTF-8"?>
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<PMML xmlns="http://www.dmg.org/PMML-4_4" version="4.4.1">
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<Header copyright="Copyright IBM Corp, exported to PMML by Nyoka (c) 2022 Software AG" description="Default description">
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<Application name="SimpleRuleSetExport" version="0.0.1"/>
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<Timestamp>1970-01-01 00:00:00+00:00</Timestamp>
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</Header>
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<DataDictionary numberOfFields="14">
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<DataField name="age" optype="continuous" dataType="double"/>
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<DataField name="workclass" optype="categorical" dataType="string">
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<Value value="Private"/>
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<Value value="State-gov"/>
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<Value value="Self-emp-not-inc"/>
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<Value value="Local-gov"/>
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<Value value="Federal-gov"/>
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<Value value="Self-emp-inc"/>
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<Value value="Without-pay"/>
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</DataField>
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<DataField name="fnlwgt" optype="continuous" dataType="double"/>
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<DataField name="education" optype="categorical" dataType="string">
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<Value value="HS-grad"/>
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<Value value="10th"/>
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<Value value="Bachelors"/>
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<Value value="Assoc-acdm"/>
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<Value value="Some-college"/>
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<Value value="Doctorate"/>
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<Value value="Prof-school"/>
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<Value value="9th"/>
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<Value value="Assoc-voc"/>
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<Value value="Masters"/>
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<Value value="7th-8th"/>
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<Value value="11th"/>
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<Value value="1st-4th"/>
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<Value value="5th-6th"/>
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<Value value="12th"/>
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<Value value="Preschool"/>
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</DataField>
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<DataField name="education_num" optype="continuous" dataType="double"/>
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<DataField name="marital_status" optype="categorical" dataType="string">
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<Value value="Married-civ-spouse"/>
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<Value value="Divorced"/>
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<Value value="Never-married"/>
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<Value value="Widowed"/>
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<Value value="Separated"/>
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<Value value="Married-spouse-absent"/>
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<Value value="Married-AF-spouse"/>
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</DataField>
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<DataField name="occupation" optype="categorical" dataType="string">
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<Value value="Transport-moving"/>
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<Value value="Craft-repair"/>
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<Value value="Sales"/>
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<Value value="Adm-clerical"/>
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<Value value="Prof-specialty"/>
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<Value value="Other-service"/>
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<Value value="Exec-managerial"/>
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<Value value="Farming-fishing"/>
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<Value value="Machine-op-inspct"/>
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<Value value="Handlers-cleaners"/>
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<Value value="Protective-serv"/>
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<Value value="Tech-support"/>
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<Value value="Priv-house-serv"/>
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<Value value="Armed-Forces"/>
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</DataField>
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<DataField name="relationship" optype="categorical" dataType="string">
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<Value value="Husband"/>
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<Value value="Not-in-family"/>
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<Value value="Wife"/>
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<Value value="Own-child"/>
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<Value value="Unmarried"/>
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<Value value="Other-relative"/>
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</DataField>
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<DataField name="race" optype="categorical" dataType="string">
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<Value value="White"/>
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<Value value="Black"/>
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<Value value="Other"/>
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<Value value="Asian-Pac-Islander"/>
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<Value value="Amer-Indian-Eskimo"/>
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</DataField>
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<DataField name="sex" optype="categorical" dataType="string">
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<Value value="Male"/>
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<Value value="Female"/>
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</DataField>
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<DataField name="capital_gain" optype="continuous" dataType="double"/>
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<DataField name="capital_loss" optype="continuous" dataType="double"/>
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<DataField name="hours_per_week" optype="continuous" dataType="double"/>
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<DataField name="native_country" optype="categorical" dataType="string">
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<Value value="United-States"/>
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<Value value="Portugal"/>
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<Value value="Cuba"/>
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<Value value="Mexico"/>
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<Value value="France"/>
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<Value value="Jamaica"/>
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<Value value="Haiti"/>
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<Value value="Honduras"/>
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<Value value="India"/>
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<Value value="Dominican-Republic"/>
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<Value value="Outlying-US(Guam-USVI-etc)"/>
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<Value value="South"/>
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<Value value="Scotland"/>
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<Value value="Italy"/>
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<Value value="Germany"/>
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<Value value="Philippines"/>
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<Value value="Vietnam"/>
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<Value value="El-Salvador"/>
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<Value value="Nicaragua"/>
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<Value value="China"/>
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<Value value="Trinadad&amp;Tobago"/>
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<Value value="Puerto-Rico"/>
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<Value value="Japan"/>
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<Value value="Iran"/>
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<Value value="Guatemala"/>
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<Value value="England"/>
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<Value value="Poland"/>
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<Value value="Canada"/>
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<Value value="Cambodia"/>
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<Value value="Greece"/>
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<Value value="Thailand"/>
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<Value value="Ireland"/>
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<Value value="Hong"/>
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<Value value="Taiwan"/>
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<Value value="Ecuador"/>
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<Value value="Peru"/>
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<Value value="Yugoslavia"/>
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<Value value="Columbia"/>
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<Value value="Hungary"/>
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<Value value="Laos"/>
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<Value value="Holand-Netherlands"/>
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</DataField>
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</DataDictionary>
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<RuleSetModel functionName="classification" algorithmName="RuleSet">
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<MiningSchema>
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<MiningField name="marital_status" usageType="active"/>
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<MiningField name="education_num" usageType="active"/>
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<MiningField name="hours_per_week" usageType="active"/>
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<MiningField name="education" usageType="active"/>
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<MiningField name="age" usageType="active"/>
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<MiningField name="occupation" usageType="active"/>
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<MiningField name="fnlwgt" usageType="active"/>
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<MiningField name="capital_gain" usageType="active"/>
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<MiningField name="capital_loss" usageType="active"/>
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</MiningSchema>
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<RuleSet defaultScore="&lt;=50K">
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<RuleSelectionMethod criterion="weightedMax"/>
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<SimpleRule id="[marital_status == Married-civ-spouse] ^ [education_num &lt;= 12.0] ^ [education_num &gt;= 8.0] ^ [hours_per_week &gt;= 38.0] ^ [education == Some-college] ^ [age &lt;= 57.0] ^ [hours_per_week &lt;= 45.0] ^ [age &gt;= 48.0]" score="&gt;50K" recordCount="15081" nbCorrect="11329" confidence="0.609271523178808" weight="0.609271523178808">
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<CompoundPredicate booleanOperator="and">
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<SimplePredicate field="marital_status" operator="equal" value="Married-civ-spouse"/>
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<SimplePredicate field="education_num" operator="lessOrEqual" value="12.0"/>
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<SimplePredicate field="education_num" operator="greaterOrEqual" value="8.0"/>
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<SimplePredicate field="hours_per_week" operator="greaterOrEqual" value="38.0"/>
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<SimplePredicate field="education" operator="equal" value="Some-college"/>
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<SimplePredicate field="age" operator="lessOrEqual" value="57.0"/>
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<SimplePredicate field="hours_per_week" operator="lessOrEqual" value="45.0"/>
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<SimplePredicate field="age" operator="greaterOrEqual" value="48.0"/>
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</CompoundPredicate>
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</SimpleRule>
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<SimpleRule id="[marital_status == Married-civ-spouse] ^ [education_num &lt;= 12.0] ^ [age &gt;= 37.0] ^ [occupation == Tech-support]" score="&gt;50K" recordCount="15081" nbCorrect="11323" confidence="0.684931506849315" weight="0.684931506849315">
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<CompoundPredicate booleanOperator="and">
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<SimplePredicate field="marital_status" operator="equal" value="Married-civ-spouse"/>
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<SimplePredicate field="education_num" operator="lessOrEqual" value="12.0"/>
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<SimplePredicate field="age" operator="greaterOrEqual" value="37.0"/>
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<SimplePredicate field="occupation" operator="equal" value="Tech-support"/>
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</CompoundPredicate>
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</SimpleRule>
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<SimpleRule id="[marital_status == Married-civ-spouse] ^ [education_num &lt;= 12.0] ^ [education_num &gt;= 9.0] ^ [hours_per_week &gt;= 40.0] ^ [age &gt;= 42.0] ^ [education == HS-grad] ^ [age &lt;= 53.0] ^ [fnlwgt &gt;= 154227.0] ^ [fnlwgt &lt;= 163948.0]" score="&gt;50K" recordCount="15081" nbCorrect="11287" confidence="0.3448275862068966" weight="0.3448275862068966">
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<CompoundPredicate booleanOperator="and">
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<SimplePredicate field="marital_status" operator="equal" value="Married-civ-spouse"/>
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<SimplePredicate field="education_num" operator="lessOrEqual" value="12.0"/>
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<SimplePredicate field="education_num" operator="greaterOrEqual" value="9.0"/>
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<SimplePredicate field="hours_per_week" operator="greaterOrEqual" value="40.0"/>
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<SimplePredicate field="age" operator="greaterOrEqual" value="42.0"/>
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<SimplePredicate field="education" operator="equal" value="HS-grad"/>
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<SimplePredicate field="age" operator="lessOrEqual" value="53.0"/>
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<SimplePredicate field="fnlwgt" operator="greaterOrEqual" value="154227.0"/>
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<SimplePredicate field="fnlwgt" operator="lessOrEqual" value="163948.0"/>
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</CompoundPredicate>
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</SimpleRule>
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<SimpleRule id="[marital_status == Married-civ-spouse] ^ [age &gt;= 37.0] ^ [education_num &lt;= 12.0] ^ [age &lt;= 47.0] ^ [education_num &gt;= 10.0] ^ [occupation == Sales] ^ [fnlwgt &gt;= 131827.0]" score="&gt;50K" recordCount="15081" nbCorrect="11300" confidence="0.5333333333333333" weight="0.5333333333333333">
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<CompoundPredicate booleanOperator="and">
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<SimplePredicate field="marital_status" operator="equal" value="Married-civ-spouse"/>
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<SimplePredicate field="age" operator="greaterOrEqual" value="37.0"/>
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<SimplePredicate field="education_num" operator="lessOrEqual" value="12.0"/>
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<SimplePredicate field="age" operator="lessOrEqual" value="47.0"/>
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<SimplePredicate field="education_num" operator="greaterOrEqual" value="10.0"/>
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<SimplePredicate field="occupation" operator="equal" value="Sales"/>
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<SimplePredicate field="fnlwgt" operator="greaterOrEqual" value="131827.0"/>
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</CompoundPredicate>
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</SimpleRule>
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<SimpleRule id="[marital_status == Married-civ-spouse] ^ [education_num &gt;= 13.0]" score="&gt;50K" recordCount="15081" nbCorrect="12283" confidence="0.7355608591885442" weight="0.7355608591885442">
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<CompoundPredicate booleanOperator="and">
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<SimplePredicate field="marital_status" operator="equal" value="Married-civ-spouse"/>
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<SimplePredicate field="education_num" operator="greaterOrEqual" value="13.0"/>
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</CompoundPredicate>
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</SimpleRule>
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<SimpleRule id="[marital_status == Married-civ-spouse] ^ [capital_gain &gt;= 5178.0]" score="&gt;50K" recordCount="15081" nbCorrect="11863" confidence="0.9913344887348353" weight="0.9913344887348353">
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<CompoundPredicate booleanOperator="and">
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<SimplePredicate field="marital_status" operator="equal" value="Married-civ-spouse"/>
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<SimplePredicate field="capital_gain" operator="greaterOrEqual" value="5178.0"/>
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</CompoundPredicate>
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</SimpleRule>
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<SimpleRule id="[marital_status == Married-civ-spouse] ^ [education_num &lt;= 12.0] ^ [capital_loss &gt;= 1741.0]" score="&gt;50K" recordCount="15081" nbCorrect="11370" confidence="0.6968085106382979" weight="0.6968085106382979">
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<CompoundPredicate booleanOperator="and">
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<SimplePredicate field="marital_status" operator="equal" value="Married-civ-spouse"/>
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<SimplePredicate field="education_num" operator="lessOrEqual" value="12.0"/>
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<SimplePredicate field="capital_loss" operator="greaterOrEqual" value="1741.0"/>
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</CompoundPredicate>
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</SimpleRule>
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<SimpleRule id="[marital_status == Married-civ-spouse] ^ [education_num &gt;= 10.0] ^ [fnlwgt &gt;= 118088.0] ^ [occupation == Exec-managerial] ^ [hours_per_week &gt;= 41.0]" score="&gt;50K" recordCount="15081" nbCorrect="11535" confidence="0.8103896103896104" weight="0.8103896103896104">
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<CompoundPredicate booleanOperator="and">
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<SimplePredicate field="marital_status" operator="equal" value="Married-civ-spouse"/>
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<SimplePredicate field="education_num" operator="greaterOrEqual" value="10.0"/>
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<SimplePredicate field="fnlwgt" operator="greaterOrEqual" value="118088.0"/>
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<SimplePredicate field="occupation" operator="equal" value="Exec-managerial"/>
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<SimplePredicate field="hours_per_week" operator="greaterOrEqual" value="41.0"/>
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</CompoundPredicate>
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</SimpleRule>
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</RuleSet>
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</RuleSetModel>
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</PMML>

‎tests/rule_induction/trxf/pmml_export/test_pmml_exporter.py‎

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import datetime
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import os
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import sys
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from unittest import TestCase
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import pandas as pd
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reader.load_data_dictionary(x_test)
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serializer = NyokaSerializer(TIMESTAMP)
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exporter = PmmlExporter(reader, serializer)
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with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'resources/adult.pmml')) as file:
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filename = 'adult.pmml' if sys.version_info[1] > 6 else 'adult_py36.pmml'
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with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'resources', filename)) as file:
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expected = file.read()
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actual = exporter.export(classifier)
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self.assertEqual(expected, actual)

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