/** * Gets the currently set performance evaluation measure used for selecting * attributes for the decision table * * @return the performance evaluation measure */ public SelectedTag getEvaluationMeasure() { return new SelectedTag(m_evaluationMeasure, TAGS_EVALUATION); }
/** * Set the loss function to use. * * @param function the loss function to use. */ public void setLossFunction(SelectedTag function) { if (function.getTags() == TAGS_SELECTION) { m_loss = function.getSelectedTag().getID(); } }
/** * Returns whether predictions can be discarded (depends on selected measure). */ protected boolean canDiscardPredictions() { switch (m_Owner.getEvaluation().getSelectedTag().getID()) { case DefaultEvaluationMetrics.EVALUATION_AUC: case DefaultEvaluationMetrics.EVALUATION_PRC: return false; default: return true; } }
/** * Sets the attribute type to be deleted by the filter. * * @param type a TAGS_ATTRIBUTETYPE of the new type the filter should delete */ public void setAttributeType(SelectedTag type) { if (type.getTags() == TAGS_ATTRIBUTETYPE) { m_attTypeToDelete = type.getSelectedTag().getID(); } }
/** * Gets the current value as text. * * @return a value of type 'String' */ public String getAsText() { SelectedTag s = (SelectedTag)getValue(); return s.getSelectedTag().getReadable(); }
/** * Sets how the training data will be transformed. Should be one of * FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE. * * @param newType the new filtering mode */ public void setFilterType(SelectedTag newType) { if (newType.getTags() == TAGS_FILTER) { m_filterType = newType.getSelectedTag().getID(); } }
/** * Gets the method used. Will be one of METHOD_1_AGAINST_ALL, * METHOD_ERROR_RANDOM, METHOD_ERROR_EXHAUSTIVE, or METHOD_1_AGAINST_1. * * @return the current method. */ public SelectedTag getMethod() { return new SelectedTag(m_Method, TAGS_METHOD); }
/** * Sets the pattern type. * * @param value new pattern type */ public void setPattern(SelectedTag value) { if (value.getTags() == TAGS_PATTERN) { m_Pattern = value.getSelectedTag().getID(); } }
/** * Get the metric type * * @return the type of metric to use for ranking rules */ public SelectedTag getMetricType() { return new SelectedTag(m_metricType, TAGS_SELECTION); }
/** * The new method for weighting the instances. * * @param method the new method */ public void setWeightMethod(SelectedTag method) { if (method.getTags() == TAGS_WEIGHTMETHOD) { m_WeightMethod = method.getSelectedTag().getID(); } }
/** * Gets the method used for pruning. * * @return the pruning method to use. */ public SelectedTag getPruningMethod() { return new SelectedTag(m_PruningMethod, TAGS_PRUNING); }
/** * Sets the algorithm type. * * @param newType the new algorithm type */ public void setAlgorithmType(SelectedTag newType) { if (newType.getTags() == TAGS_ALGORITHMTYPE) { m_AlgorithmType = newType.getSelectedTag().getID(); } }
/** * Gets the source location method of the cost matrix. Will be one of * MATRIX_ON_DEMAND or MATRIX_SUPPLIED. * * @return the cost matrix source. */ public SelectedTag getCostMatrixSource() { return new SelectedTag(m_MatrixSource, TAGS_MATRIX_SOURCE); }
/** * Sets how the training data will be transformed. Should be one of * FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE. * * @param newType the new filtering mode */ public void setFilterType(SelectedTag newType) { if (newType.getTags() == TAGS_FILTER) { m_filterType = newType.getSelectedTag().getID(); } }
/** * Gets the estimator * * @return the estimator */ public SelectedTag getEstimator() { return new SelectedTag(paceEstimator, TAGS_ESTIMATOR); }
/** * The new method for weighting the instances. * * @param method the new method */ public void setWeightMethod(SelectedTag method) { if (method.getTags() == MultiInstanceToPropositional.TAGS_WEIGHTMETHOD) { m_WeightMethod = method.getSelectedTag().getID(); } }
/** * Gets how the training data will be transformed. Will be one of * FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE. * * @return the filtering mode */ public SelectedTag getFilterType() { return new SelectedTag(m_filterType, TAGS_FILTER); }
/** * Sets how the training data will be transformed. Should be one of * FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE. * * @param newType the new filtering mode */ public void setFilterType(SelectedTag newType) { if (newType.getTags() == TAGS_FILTER) { m_filterType = newType.getSelectedTag().getID(); } }
/** * Gets the type of algorithm. * * @return the algorithm type */ public SelectedTag getAlgorithmType() { return new SelectedTag(m_AlgorithmType, TAGS_ALGORITHMTYPE); }
/** * Sets the performance evaluation measure to use for selecting attributes for * the decision table * * @param newMethod the new performance evaluation metric to use */ public void setEvaluationMeasure(SelectedTag newMethod) { if (newMethod.getTags() == TAGS_EVALUATION) { m_evaluationMeasure = newMethod.getSelectedTag().getID(); } }