/** * Gets the current settings of the OneR classifier. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> options = new Vector<String>(1); options.add("-B"); options.add("" + m_minBucketSize); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> result = new Vector<String>(); result.add("-N"); result.add("" + m_filterType); Collections.addAll(result, super.getOptions()); return result.toArray(new String[result.size()]); }
/** * Gets the current settings of the OneR classifier. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> options = new Vector<String>(1); options.add("-B"); options.add("" + m_minBucketSize); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> result = new Vector<String>(); result.add("-N"); result.add("" + m_filterType); Collections.addAll(result, super.getOptions()); return result.toArray(new String[result.size()]); }
/** * Gets the current settings of IBk. * * @return an array of strings suitable for passing to setOptions() */ public String [] getOptions() { java.util.Vector<String> options = new java.util.Vector<String>(); options.add("-R"); options.add("" + getRidge()); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of IBk. * * @return an array of strings suitable for passing to setOptions() */ public String [] getOptions() { java.util.Vector<String> options = new java.util.Vector<String>(); options.add("-R"); options.add("" + getRidge()); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ public String [] getOptions() { Vector<String> options = new Vector<String>(); options.add("-S"); options.add("" + getSeed()); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ public String[] getOptions() { Vector<String> options = new Vector<String>(); options.add("-I"); options.add("" + m_NumIterations); options.add("-E"); options.add("" + m_Exponent); options.add("-S"); options.add("" + m_Seed); options.add("-M"); options.add("" + m_MaxK); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ public String[] getOptions() { Vector<String> options = new Vector<String>(); options.add("-I"); options.add("" + m_NumIterations); options.add("-E"); options.add("" + m_Exponent); options.add("-S"); options.add("" + m_Seed); options.add("-M"); options.add("" + m_MaxK); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ public String [] getOptions() { Vector<String> options = new Vector<String>(); options.add("-S"); options.add("" + getSeed()); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of IBk. * * @return an array of strings suitable for passing to setOptions() */ public String [] getOptions() { java.util.Vector<String> options = new java.util.Vector<String>(); options.add("-R"); options.add("" + getRidge()); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * returns the options of the current setup * * @return the current options */ @Override public String[] getOptions() { Vector<String> result = new Vector<String>(); result.add("-model"); result.add("" + getModelFile()); Collections.addAll(result, super.getOptions()); return result.toArray(new String[result.size()]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> options = new Vector<String>(); options.add("-G"); options.add("" + getnOfGaussianHiddenVars_()); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of the Classifier. * * @return an array of strings suitable for passing to setOptions */ public String [] getOptions() { Vector<String> options = new Vector<String>(); for (int i = 0; i < m_Classifiers.length; i++) { options.add("-B"); options.add("" + getClassifierSpec(i)); } Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * returns the options of the current setup * * @return the current options */ @Override public String[] getOptions() { Vector<String> result = new Vector<String>(); result.add("-model"); result.add("" + getModelFile()); Collections.addAll(result, super.getOptions()); return result.toArray(new String[result.size()]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> result = new Vector<String>(); if (getOutputAdditionalStats()) { result.add("-additional-stats"); } Collections.addAll(result, super.getOptions()); return result.toArray(new String[result.size()]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> result = new Vector<String>(); if (getOutputAdditionalStats()) { result.add("-additional-stats"); } Collections.addAll(result, super.getOptions()); return result.toArray(new String[result.size()]); }
/** * Gets the current settings of the Classifier. * * @return an array of strings suitable for passing to setOptions */ public String [] getOptions() { Vector<String> options = new Vector<String>(); for (int i = 0; i < m_Classifiers.length; i++) { options.add("-B"); options.add("" + getClassifierSpec(i)); } Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
/** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> options = new Vector<String>(); options.add("-G"); options.add("" + getnOfGaussianHiddenVars_()); options.add("-S"); options.add("" + getnOfStatesMultHiddenVar_()); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); }
public Link2(int chain[], int j, Instances train) throws Exception { this.j = j; this.index = chain[j]; // sort out excludes [4|5,1,0,2,3] this.excld = Arrays.copyOfRange(chain,j+1,chain.length); // sort out excludes [0,1,2,3,5] Arrays.sort(this.excld); //Instances new_train = new Instances(train); Instances new_train = CCUtils.linkTransform(train,j,this.index,this.excld); _template = new Instances(new_train,0); this.classifier = (AbstractClassifier)AbstractClassifier.forName(getClassifier().getClass().getName(),((AbstractClassifier)getClassifier()).getOptions()); this.classifier.buildClassifier(new_train); new_train = null; if(j+1 < chain.length) next = new Link2(chain, ++j, train); }