sklearn.Classifier.java Source code

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Here is the source code for sklearn.Classifier.java

Source

/*
 * Copyright (c) 2015 Villu Ruusmann
 *
 * This file is part of JPMML-SkLearn
 *
 * JPMML-SkLearn 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-SkLearn 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-SkLearn.  If not, see <http://www.gnu.org/licenses/>.
 */
package sklearn;

import java.util.ArrayList;
import java.util.List;

import com.google.common.base.CharMatcher;
import com.google.common.base.Function;
import com.google.common.collect.Lists;
import org.dmg.pmml.DataType;
import org.dmg.pmml.OpType;
import org.jpmml.converter.Schema;
import org.jpmml.converter.ValueUtil;
import org.jpmml.sklearn.ClassDictUtil;
import org.jpmml.sklearn.FeatureMapper;

abstract public class Classifier extends Estimator {

    public Classifier(String module, String name) {
        super(module, name);
    }

    @Override
    public Schema createSchema(FeatureMapper featureMapper) {
        List<?> classes = getClasses();

        if (classes == null || classes.isEmpty()) {
            throw new IllegalArgumentException();
        }

        DataType dataType = TypeUtil.getDataType(classes, DataType.STRING);

        List<String> targetCategories = formatTargetCategories(classes);

        if (featureMapper.isEmpty()) {
            featureMapper.initActiveFields(createActiveFields(getNumberOfFeatures()), getOpType(), getDataType());
            featureMapper.initTargetField(createTargetField(), OpType.CATEGORICAL, dataType, targetCategories);
        } else

        {
            featureMapper.updateActiveFields(getNumberOfFeatures(), true, getOpType(), getDataType());
            featureMapper.updateTargetField(OpType.CATEGORICAL, dataType, targetCategories);
        }

        Schema schema = featureMapper.createSupervisedSchema();

        if (requiresContinuousInput()) {
            schema = featureMapper.cast(OpType.CONTINUOUS, getDataType(), schema);
        }

        return schema;
    }

    public boolean hasProbabilityDistribution() {
        return true;
    }

    public List<?> getClasses() {
        return ClassDictUtil.getArray(this, "classes_");
    }

    static private List<String> formatTargetCategories(List<?> objects) {
        Function<Object, String> function = new Function<Object, String>() {

            @Override
            public String apply(Object object) {
                String targetCategory = ValueUtil.formatValue(object);

                if (targetCategory == null || CharMatcher.WHITESPACE.matchesAnyOf(targetCategory)) {
                    throw new IllegalArgumentException(targetCategory);
                }

                return targetCategory;
            }
        };

        return new ArrayList<>(Lists.transform(objects, function));
    }
}