/** * Updates stats in the cross-validation case * * @param train the training data processed * @param evaluator the evaluator used * @param search the search strategy * @param selectedAtts the attributes selected on this training data * @throws Exception if a problem occurs */ protected synchronized void updateXValStats(Instances train, ASEvaluation evaluator, ASSearch search, int[] selectedAtts) throws Exception { m_eval.updateStatsForModelCVSplit(train, evaluator, search, selectedAtts, m_isRanking); }
/** * Updates stats in the cross-validation case * * @param train the training data processed * @param evaluator the evaluator used * @param search the search strategy * @param selectedAtts the attributes selected on this training data * @throws Exception if a problem occurs */ protected synchronized void updateXValStats(Instances train, ASEvaluation evaluator, ASSearch search, int[] selectedAtts) throws Exception { m_eval.updateStatsForModelCVSplit(train, evaluator, search, selectedAtts, m_isRanking); }
/** * Select attributes for a split of the data. Calling this function updates * the statistics on attribute selection. CVResultsString() returns a string * summarizing the results of repeated calls to this function. Assumes that * splits are from the same dataset--- ie. have the same number and types of * attributes as previous splits. * * @param split the instances to select attributes from * @exception Exception if an error occurs */ public void selectAttributesCVSplit(Instances split) throws Exception { m_ASEvaluator.buildEvaluator(split); // Do the search int[] attributeSet = m_searchMethod.search(m_ASEvaluator, split); // Do any postprocessing that a attribute selection method might // require attributeSet = m_ASEvaluator.postProcess(attributeSet); updateStatsForModelCVSplit(split, m_ASEvaluator, m_searchMethod, attributeSet, m_doRank); }
/** * Select attributes for a split of the data. Calling this function updates * the statistics on attribute selection. CVResultsString() returns a string * summarizing the results of repeated calls to this function. Assumes that * splits are from the same dataset--- ie. have the same number and types of * attributes as previous splits. * * @param split the instances to select attributes from * @exception Exception if an error occurs */ public void selectAttributesCVSplit(Instances split) throws Exception { m_ASEvaluator.buildEvaluator(split); // Do the search int[] attributeSet = m_searchMethod.search(m_ASEvaluator, split); // Do any postprocessing that a attribute selection method might // require attributeSet = m_ASEvaluator.postProcess(attributeSet); updateStatsForModelCVSplit(split, m_ASEvaluator, m_searchMethod, attributeSet, m_doRank); }