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JPMML Apache Spark ML to PMML converter
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/*
* Copyright (c) 2017 Villu Ruusmann
*
* This file is part of JPMML-SparkML
*
* JPMML-SparkML is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* JPMML-SparkML is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with JPMML-SparkML. If not, see .
*/
package org.jpmml.sparkml.feature;
import java.util.ArrayList;
import java.util.List;
import org.apache.spark.ml.feature.MaxAbsScalerModel;
import org.apache.spark.ml.linalg.Vector;
import org.dmg.pmml.DataType;
import org.dmg.pmml.DerivedField;
import org.dmg.pmml.Expression;
import org.dmg.pmml.OpType;
import org.dmg.pmml.PMMLFunctions;
import org.jpmml.converter.ContinuousFeature;
import org.jpmml.converter.ExpressionUtil;
import org.jpmml.converter.Feature;
import org.jpmml.converter.SchemaUtil;
import org.jpmml.converter.ValueUtil;
import org.jpmml.sparkml.FeatureConverter;
import org.jpmml.sparkml.SparkMLEncoder;
public class MaxAbsScalerModelConverter extends FeatureConverter {
public MaxAbsScalerModelConverter(MaxAbsScalerModel transformer){
super(transformer);
}
@Override
public List encodeFeatures(SparkMLEncoder encoder){
MaxAbsScalerModel transformer = getTransformer();
Vector maxAbs = transformer.maxAbs();
List features = encoder.getFeatures(transformer.getInputCol());
SchemaUtil.checkSize(maxAbs.size(), features);
List result = new ArrayList<>();
for(int i = 0, length = features.size(); i < length; i++){
Feature feature = features.get(i);
double maxAbsUnzero = maxAbs.apply(i);
if(maxAbsUnzero == 0d){
maxAbsUnzero = 1d;
} // End if
if(!ValueUtil.isOne(maxAbsUnzero)){
ContinuousFeature continuousFeature = feature.toContinuousFeature();
Expression expression = ExpressionUtil.createApply(PMMLFunctions.DIVIDE, continuousFeature.ref(), ExpressionUtil.createConstant(maxAbsUnzero));
DerivedField derivedField = encoder.createDerivedField(formatName(transformer, i, length), OpType.CONTINUOUS, DataType.DOUBLE, expression);
feature = new ContinuousFeature(encoder, derivedField);
}
result.add(feature);
}
return result;
}
}
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