📄 featureselector.java
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package dragon.ir.classification.featureselection;import dragon.ir.classification.DocClassSet;import dragon.ir.index.IndexReader;import dragon.matrix.SparseMatrix;/** * <p>Interface of feature selector which often work tegether with text classifiers.</p> * <p></p> * <p>Copyright: Copyright (c) 2005</p> * <p>Company: IST, Drexel University</p> * @author Davis Zhou * @version 1.0 */public interface FeatureSelector { /** * This method chooses a subset of features for text classification. Some implmentations * such as DocFrequencySelector and InfoGainFeatureSelector do not support this method. * @param doctermMatrix the document-term matrix a classifer is working on * @param trainingSet the labeled training document set */ public void train(SparseMatrix doctermMatrix, DocClassSet trainingSet); /** * This method chooses a subset of features for text classification * @param indexReader the index reader a classifer is working on * @param trainingSet the labeled training document set */ public void train(IndexReader indexReader, DocClassSet trainingSet); /** * @param originalFeatureIndex the index of the feature in the old feature space * @return true if the given feature is selected for text classification */ public boolean isSelected(int originalFeatureIndex); /** * @return the number of selected features */ public int getSelectedFeatureNum(); /** * Map the old feature index to the index in the new feature space. * @param originalFeatureIndex the index of the feature before feature selection * @return the index of the feature the new space. If the feature is not selected, it will return -1. */ public int map(int originalFeatureIndex); /** * Manually set selected features. Usually used in testing stage. * @param selectedFeatures each elements contains the index of the selected feature in the old feature space. * The selected feature must be in the ascending order in the input array. */ public void setSelectedFeatures(int[] selectedFeatures);}
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