Text Classification example in datumbox - Java Machine Learning AI

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Description

Text Classification example in datumbox

Demo Code

/**//from w w w. j  a v  a2 s . c o m
 * Copyright (C) 2013-2015 Vasilis Vryniotis <bbriniotis@datumbox.com>
 *
 * Licensed 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 "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

import com.datumbox.applications.nlp.TextClassifier;
import com.datumbox.common.dataobjects.Record;
import com.datumbox.common.persistentstorage.ConfigurationFactory;
import com.datumbox.common.persistentstorage.interfaces.DatabaseConfiguration;
import com.datumbox.common.utilities.PHPfunctions;
import com.datumbox.common.utilities.RandomGenerator;
import com.datumbox.framework.machinelearning.classification.MultinomialNaiveBayes;
import com.datumbox.framework.machinelearning.common.bases.mlmodels.BaseMLmodel;
import com.datumbox.framework.machinelearning.featureselection.categorical.ChisquareSelect;
import com.datumbox.framework.utilities.text.extractors.NgramsExtractor;

import java.net.URI;
import java.net.URISyntaxException;
import java.util.HashMap;
import java.util.Map;

/**
 * Text Classification example.
 * 
 * @author Vasilis Vryniotis <bbriniotis@datumbox.com>
 */
public class TextClassification {

    /**
     * Example of how to use the TextClassifier class.
     * 
     * @param args the command line arguments
     * @throws URISyntaxException
     */
    public static void main(String[] args) throws URISyntaxException {
        /**
         * There are two configuration files in the resources folder:
         * 
         * - datumbox.config.properties: It contains the configuration for the storage engines (required)
         * - logback.xml: It contains the configuration file for the logger (optional)
         */

        //Initialization
        //--------------
        RandomGenerator.setGlobalSeed(42L); //optionally set a specific seed for all Random objects
        DatabaseConfiguration dbConf = ConfigurationFactory.INMEMORY
                .getConfiguration(); //in-memory maps
        //DatabaseConfiguration dbConf = ConfigurationFactory.MAPDB.getConfiguration(); //mapdb maps

        //Reading Data
        //------------
        Map<Object, URI> dataset = new HashMap<>(); //The examples of each category are stored on the same file, one example per row.
        dataset.put("positive", TextClassification.class.getClassLoader()
                .getResource("datasets/sentiment-analysis/rt-polarity.pos")
                .toURI());
        dataset.put("negative", TextClassification.class.getClassLoader()
                .getResource("datasets/sentiment-analysis/rt-polarity.neg")
                .toURI());

        //Setup Training Parameters
        //-------------------------
        TextClassifier.TrainingParameters trainingParameters = new TextClassifier.TrainingParameters();

        //Classifier configuration
        trainingParameters.setMLmodelClass(MultinomialNaiveBayes.class);
        trainingParameters
                .setMLmodelTrainingParameters(new MultinomialNaiveBayes.TrainingParameters());

        //Set data transfomation configuration
        trainingParameters.setDataTransformerClass(null);
        trainingParameters.setDataTransformerTrainingParameters(null);

        //Set feature selection configuration
        trainingParameters.setFeatureSelectionClass(ChisquareSelect.class);
        trainingParameters
                .setFeatureSelectionTrainingParameters(new ChisquareSelect.TrainingParameters());

        //Set text extraction configuration
        trainingParameters.setTextExtractorClass(NgramsExtractor.class);
        trainingParameters
                .setTextExtractorParameters(new NgramsExtractor.Parameters());

        //Fit the classifier
        //------------------
        TextClassifier classifier = new TextClassifier("SentimentAnalysis",
                dbConf);
        classifier.fit(dataset, trainingParameters);

        //Use the classifier
        //------------------

        //Get validation metrics on the training set
        BaseMLmodel.ValidationMetrics vm = classifier.validate(dataset);
        classifier.setValidationMetrics(vm); //store them in the model for future reference

        //Classify a single sentence
        String sentence = "Machine learning gives great insight!";
        Record r = classifier.predict(sentence);

        System.out.println("Classifing sentence: \"" + sentence + "\"");
        System.out.println("Predicted class: " + r.getYPredicted());
        System.out.println("Probability: "
                + r.getYPredictedProbabilities().get(r.getYPredicted()));

        System.out.println("Classifier Statistics: "
                + PHPfunctions.var_export(vm));

        //Clean up
        //--------

        //Erase the classifier. This removes all files.
        classifier.erase();
    }

}

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