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* Licensed to the Apache Software Foundation (ASF) under one
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* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
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* KIND, either express or implied. See the License for the
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package org.apache.uima.ruta.textruler.learner.rapier;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;
import org.apache.uima.ruta.textruler.extension.TextRulerLearner;
import org.apache.uima.ruta.textruler.extension.TextRulerLearnerDelegate;
import org.apache.uima.ruta.textruler.extension.TextRulerLearnerFactory;
import org.apache.uima.ruta.textruler.extension.TextRulerLearnerParameter;
import org.apache.uima.ruta.textruler.extension.TextRulerLearnerParameter.MLAlgorithmParamType;
public class RapierFactory implements TextRulerLearnerFactory {
public TextRulerLearner createAlgorithm(String inputFolderPath, String additionalFolderPath,
String prePropTMFile, String tempFolderPath, String[] fullSlotTypeNames,
Set<String> filterSet, boolean skip, TextRulerLearnerDelegate delegate) {
return new Rapier(inputFolderPath, prePropTMFile, tempFolderPath, fullSlotTypeNames, filterSet,
skip, delegate);
}
public TextRulerLearnerParameter[] getAlgorithmParameters() {
TextRulerLearnerParameter[] result = new TextRulerLearnerParameter[8];
result[0] = new TextRulerLearnerParameter(Rapier.COMPRESSION_FAIL_MAX_COUNT_KEY,
"Maximum Compression Fail Count", MLAlgorithmParamType.ML_INT_PARAM);
result[1] = new TextRulerLearnerParameter(Rapier.RULELIST_SIZE_KEY, "Internal Rules List Size",
MLAlgorithmParamType.ML_INT_PARAM);
result[2] = new TextRulerLearnerParameter(Rapier.PAIR_COUNT_KEY, "Rule Pairs for Generalizing",
MLAlgorithmParamType.ML_INT_PARAM);
result[3] = new TextRulerLearnerParameter(Rapier.LIM_NO_IMPROVEMENTS_KEY,
"Maximum 'No improvement' Count", MLAlgorithmParamType.ML_INT_PARAM);
result[4] = new TextRulerLearnerParameter(Rapier.NOISE_THESHOLD_KEY, "Maximum Noise Threshold",
MLAlgorithmParamType.ML_FLOAT_PARAM);
result[5] = new TextRulerLearnerParameter(Rapier.MIN_COVERED_POSITIVES_KEY,
"Minimum Covered Positives Per Rule", MLAlgorithmParamType.ML_INT_PARAM);
result[6] = new TextRulerLearnerParameter(Rapier.POSTAG_ROOTTYPE_KEY, "PosTag Root Type",
MLAlgorithmParamType.ML_STRING_PARAM);
result[7] = new TextRulerLearnerParameter(Rapier.USE_ALL_GENSETS_AT_SPECIALIZATION_KEY,
"Use All 3 GenSets at Specialization", MLAlgorithmParamType.ML_BOOL_PARAM);
return result;
}
public Map<String, Object> getAlgorithmParameterStandardValues() {
Map<String, Object> result = new HashMap<String, Object>();
result.put(Rapier.COMPRESSION_FAIL_MAX_COUNT_KEY, Rapier.STANDARD_COMPRESSION_FAIL_MAX_COUNT);
result.put(Rapier.RULELIST_SIZE_KEY, Rapier.STANDARD_RULELIST_SIZE);
result.put(Rapier.PAIR_COUNT_KEY, Rapier.STANDARD_PAIR_COUNT);
result.put(Rapier.LIM_NO_IMPROVEMENTS_KEY, Rapier.STANDARD_LIM_NO_IMPROVEMENTS);
result.put(Rapier.NOISE_THESHOLD_KEY, Rapier.STANDARD_NOISE_THREHSOLD);
result.put(Rapier.POSTAG_ROOTTYPE_KEY, Rapier.STANDARD_POSTAG_ROOTTYPE);
result.put(Rapier.MIN_COVERED_POSITIVES_KEY, Rapier.STANDARD_MIN_COVERED_POSITIVES);
result.put(Rapier.USE_ALL_GENSETS_AT_SPECIALIZATION_KEY,
Rapier.STANDARD_USE_ALL_GENSETS_AT_SPECIALIZATION);
return result;
}
}