/** * Sets whether the matching sense of attribute indices is inverted or not. * * @param value if true the matching sense is inverted */ public void setInvertSelection(boolean value) { m_Remove.setInvertSelection(!value); }
/** * Sets whether the matching sense of attribute indices is inverted or not. * * @param value if true the matching sense is inverted */ public void setInvertSelection(boolean value) { m_Remove.setInvertSelection(!value); }
/** * Default constructor: need to set up Remove filter. */ public FilteredDistance() { m_Remove.setInvertSelection(true); m_Remove.setAttributeIndices("first-last"); }
/** * Default constructor: need to set up Remove filter. */ public FilteredDistance() { m_Remove.setInvertSelection(true); m_Remove.setAttributeIndices("first-last"); }
private Instances removeIgnoreCols(Instances inst, int[] toIgnore) { Remove af = new Remove(); Instances retI = null; try { af.setAttributeIndicesArray(toIgnore); af.setInvertSelection(false); af.setInputFormat(inst); retI = Filter.useFilter(inst, af); } catch (Exception e) { e.printStackTrace(); } return retI; }
private Instances removeIgnoreCols(Instances inst, int[] toIgnore) { Remove af = new Remove(); Instances retI = null; try { af.setAttributeIndicesArray(toIgnore); af.setInvertSelection(false); af.setInputFormat(inst); retI = Filter.useFilter(inst, af); } catch (Exception e) { e.printStackTrace(); } return retI; }
/** * Remove Indices - Remove attribute indices 'indices' from 'D'. * @param D Dataset * @param indices attribute indices to remove/keep * @param inv if true, then keep 'indices' * @return New dataset with 'indices' removed. */ public static Instances remove(Instances D, int indices[], boolean inv) throws Exception { Remove remove = new Remove(); remove.setAttributeIndicesArray(indices); remove.setInvertSelection(inv); remove.setInputFormat(D); return Filter.useFilter(D, remove); }
/** * Remove Indices - Remove attribute indices 'indices' from 'D'. * @param D Dataset * @param indices attribute indices to remove/keep * @param inv if true, then keep 'indices' * @return New dataset with 'indices' removed. */ public static Instances remove(Instances D, int indices[], boolean inv) throws Exception { Remove remove = new Remove(); remove.setAttributeIndicesArray(indices); remove.setInvertSelection(inv); remove.setInputFormat(D); return Filter.useFilter(D, remove); }
private Instances removeClass(Instances inst) { Remove af = new Remove(); Instances retI = null; try { if (inst.classIndex() < 0) { retI = inst; } else { af.setAttributeIndices("" + (inst.classIndex() + 1)); af.setInvertSelection(false); af.setInputFormat(inst); retI = Filter.useFilter(inst, af); } } catch (Exception e) { e.printStackTrace(); } return retI; }
/** * Returns a new set of instances either only with the labels (labels = true) or * only the features (labels = false) * * @param inst The input instances. * @param labels Return labels (true) or features (false) */ protected Instances extractPart(Instances inst, boolean labels) throws Exception{ //TODO Maybe alreade exists somewhere in Meka? Remove remove = new Remove(); remove.setAttributeIndices("first-"+(inst.classIndex())); remove.setInvertSelection(labels); remove.setInputFormat(inst); return Filter.useFilter(inst, remove); }
/** * Returns a new set of instances either only with the labels (labels = true) or * only the features (labels = false) * * @param inst The input instances. * @param labels Return labels (true) or features (false) */ protected Instances extractPart(Instances inst, boolean labels) throws Exception{ //TODO Maybe alreade exists somewhere in Meka? Remove remove = new Remove(); remove.setAttributeIndices("first-"+(inst.classIndex())); remove.setInvertSelection(labels); remove.setInputFormat(inst); return Filter.useFilter(inst, remove); }
/** * Builds the clusters */ private void buildClusterer() throws Exception { if (m_trainingSet.classIndex() < 0) { m_Clusterer.buildClusterer(m_trainingSet); } else { // class based evaluation if class attribute is set Remove removeClass = new Remove(); removeClass.setAttributeIndices("" + (m_trainingSet.classIndex() + 1)); removeClass.setInvertSelection(false); removeClass.setInputFormat(m_trainingSet); Instances clusterTrain = Filter.useFilter(m_trainingSet, removeClass); m_Clusterer.buildClusterer(clusterTrain); } }
public void testNonInverted2() { m_Filter = getFilter("first-3"); ((Remove)m_Filter).setInvertSelection(false); Instances result = useFilter(); assertEquals(m_Instances.numAttributes() - 3, result.numAttributes()); assertEquals(m_Instances.attribute(3).name(), result.attribute(0).name()); }
public void testNonInverted2() { m_Filter = getFilter("first-3"); ((Remove)m_Filter).setInvertSelection(false); Instances result = useFilter(); assertEquals(m_Instances.numAttributes() - 3, result.numAttributes()); assertEquals(m_Instances.attribute(3).name(), result.attribute(0).name()); }
public void testTypical() { m_Filter = getFilter("1,2"); ((Remove)m_Filter).setInvertSelection(true); Instances result = useFilter(); assertEquals(2, result.numAttributes()); assertEquals(m_Instances.attribute(0).name(), result.attribute(0).name()); assertEquals(m_Instances.attribute(1).name(), result.attribute(1).name()); }
public void testTypical2() { m_Filter = getFilter("3-4"); ((Remove)m_Filter).setInvertSelection(true); Instances result = useFilter(); assertEquals(2, result.numAttributes()); assertEquals(m_Instances.attribute(2).name(), result.attribute(0).name()); assertEquals(m_Instances.attribute(3).name(), result.attribute(1).name()); }
public void testTypical2() { m_Filter = getFilter("3-4"); ((Remove)m_Filter).setInvertSelection(true); Instances result = useFilter(); assertEquals(2, result.numAttributes()); assertEquals(m_Instances.attribute(2).name(), result.attribute(0).name()); assertEquals(m_Instances.attribute(3).name(), result.attribute(1).name()); }
public void testNonInverted() { m_Filter = getFilter("1,2"); ((Remove)m_Filter).setInvertSelection(false); Instances result = useFilter(); assertEquals(m_Instances.numAttributes() - 2, result.numAttributes()); assertEquals(m_Instances.attribute(2).name(), result.attribute(0).name()); assertEquals(m_Instances.attribute(3).name(), result.attribute(1).name()); }
public void testTypical() { m_Filter = getFilter("1,2"); ((Remove)m_Filter).setInvertSelection(true); Instances result = useFilter(); assertEquals(2, result.numAttributes()); assertEquals(m_Instances.attribute(0).name(), result.attribute(0).name()); assertEquals(m_Instances.attribute(1).name(), result.attribute(1).name()); }
public void testNonInverted() { m_Filter = getFilter("1,2"); ((Remove)m_Filter).setInvertSelection(false); Instances result = useFilter(); assertEquals(m_Instances.numAttributes() - 2, result.numAttributes()); assertEquals(m_Instances.attribute(2).name(), result.attribute(0).name()); assertEquals(m_Instances.attribute(3).name(), result.attribute(1).name()); }