Java Code Examples for weka.core.Utils#joinOptions()

public static String objectToCLIString(Object obj, Class<?> requiredType) {
	if (obj == null) {
		return "";
	}
	if (obj instanceof File) {
		return (FILE_PREFIX_STRING + ((File) obj).getPath());
	}
	if (obj instanceof String) {
		return (INMEM_PREFIX_STRING + obj);
	}
	String className = classToCLIString(obj.getClass(), requiredType);
	if (obj instanceof weka.core.OptionHandler) {
		String subOptions = Utils.joinOptions(((weka.core.OptionHandler) obj).getOptions());
		if (subOptions.length() > 0) {
			return new String(className + " " + subOptions).trim();
		}
	}
	return className;
}
 

/**
 * Gets the current settings of the classifier.
 *
 * @return an array of strings suitable for passing to setOptions
 */
public String [] getOptions() {

  String [] superOptions = super.getOptions();
  String [] options = new String [superOptions.length + 6];

  int current = 0;

  options[current++] = "-U"; options[current++] = "" + getWeightingKernel();
  if ( (getKNN() == 0) && m_UseAllK) {
    options[current++] = "-K"; options[current++] = "-1";
  }
  else {
    options[current++] = "-K"; options[current++] = "" + getKNN();
  }
  options[current++] = "-A";
  options[current++] = m_NNSearch.getClass().getName()+" "+Utils.joinOptions(m_NNSearch.getOptions()); 

  System.arraycopy(superOptions, 0, options, current,
                   superOptions.length);

  return options;
}
 

/**
 * Gets the current settings of the Classifier.
 *
 * @return an array of strings suitable for passing to setOptions
 */
public String [] getOptions() {

  String [] superOptions = super.getOptions();
  String [] options = new String [superOptions.length + 4];

  int current = 0;
  options[current++] = "-X"; options[current++] = "" + getNumFolds();
  options[current++] = "-M";
  options[current++] = getMetaClassifier().getClass().getName() + " "
    + Utils.joinOptions(((OptionHandler)getMetaClassifier()).getOptions());

  System.arraycopy(superOptions, 0, options, current, 
     superOptions.length);
  return options;
}
 

/**
 * returns the filter classname and the options as one string.
 *
 * @param filter	the filter to get the specs for
 * @return		the classname plus options
 */
protected String getFilterSpec(Filter filter) {
  String        result;

  if (filter == null) {
    result = "";
  }
  else {
    result  = filter.getClass().getName();
    if (filter instanceof OptionHandler)
      result += " "
        + Utils.joinOptions(((OptionHandler) filter).getOptions());
  }

  return result;
}
 

/**
 * Gets the search specification string, which contains the class name of
 * the search method and any options to it
 *
 * @return the search string.
 */
protected String getSearchSpec() {

  ASSearch s = getSearch();
  if (s instanceof OptionHandler) {
    return s.getClass().getName() + " "
    + Utils.joinOptions(((OptionHandler)s).getOptions());
  }
  return s.getClass().getName();
}
 

/**
 * Gets the current settings of IBk.
 *
 * @return an array of strings suitable for passing to setOptions()
 */
public String [] getOptions() {

  String [] options = new String [11];
  int current = 0;
  options[current++] = "-K"; options[current++] = "" + getKNN();
  options[current++] = "-W"; options[current++] = "" + m_WindowSize;
  if (getCrossValidate()) {
    options[current++] = "-X";
  }
  if (getMeanSquared()) {
    options[current++] = "-E";
  }
  if (m_DistanceWeighting == WEIGHT_INVERSE) {
    options[current++] = "-I";
  } else if (m_DistanceWeighting == WEIGHT_SIMILARITY) {
    options[current++] = "-F";
  }

  options[current++] = "-A";
  options[current++] = m_NNSearch.getClass().getName()+" "+Utils.joinOptions(m_NNSearch.getOptions()); 
  
  while (current < options.length) {
    options[current++] = "";
  }
  
  return options;
}
 

/**
  * Returns description of the cross-validated classifier.
  *
  * @return description of the cross-validated classifier as a string
  */
 public String toString() {

   if (m_InitOptions == null)
     return "CVParameterSelection: No model built yet.";

   String result = "Cross-validated Parameter selection.\n"
   + "Classifier: " + m_Classifier.getClass().getName() + "\n";
   try {
     for (int i = 0; i < m_CVParams.size(); i++) {
CVParameter cvParam = (CVParameter)m_CVParams.elementAt(i);
result += "Cross-validation Parameter: '-" 
  + cvParam.m_ParamChar + "'"
  + " ranged from " + cvParam.m_Lower 
  + " to ";
switch ((int)(cvParam.m_Lower - cvParam.m_Upper + 0.5)) {
case 1:
  result += m_NumAttributes;
  break;
case 2:
  result += m_TrainFoldSize;
  break;
default:
  result += cvParam.m_Upper;
  break;
}
result += " with " + cvParam.m_Steps + " steps\n";
     }
   } catch (Exception ex) {
     result += ex.getMessage();
   }
   result += "Classifier Options: "
     + Utils.joinOptions(m_BestClassifierOptions)
     + "\n\n" + m_Classifier.toString();
   return result;
 }
 

/**
 * Returns graph describing the classifier (if possible).
 *
 * @return the graph of the classifier in dotty format
 * @throws Exception if the classifier cannot be graphed
 */
public String graph() throws Exception {
  
  if (m_Classifier instanceof Drawable)
    return ((Drawable)m_Classifier).graph();
  else throw new Exception("Classifier: " + 
	     m_Classifier.getClass().getName() + " " +
	     Utils.joinOptions(m_BestClassifierOptions)
	     + " cannot be graphed");
}
 

/**
  * Gets the filter specification string, which contains the class name of
  * the filter and any options to the filter
  *
  * @return the filter string.
  */
 /* Taken from FilteredClassifier */
 protected String getProjectionFilterSpec() {
   
   Filter c = getProjectionFilter();
   if (c instanceof OptionHandler) {
     return c.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler)c).getOptions());
   }
   return c.getClass().getName();
 }
 

/**
  * Gets the classifier specification string, which contains the class name of
  * the classifier and any options to the classifier
  *
  * @param index the index of the classifier string to retrieve, starting from
  * 0.
  * @return the classifier string, or the empty string if no classifier
  * has been assigned (or the index given is out of range).
  */
 protected String getClassifierSpec(int index) {
   
   if (m_Classifiers.length < index) {
     return "";
   }
   Classifier c = getClassifier(index);
   if (c instanceof OptionHandler) {
     return c.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler)c).getOptions());
   }
   return c.getClass().getName();
 }
 

/**
  * Get the filter + options as a string
  *
  * @return a String containing the name of the filter + any options
  */
 protected String getFilterSpec() {
   Filter c = getFilter();
   if (c instanceof OptionHandler) {
     return c.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler)c).getOptions());
   }
   return c.getClass().getName();
 }
 

/**
  * Gets the evaluator specification string, which contains the class name of
  * the evaluator and any options to the evaluator
  *
  * @return the evaluator string.
  */
 protected String getEvaluatorSpec() {
   
   ASEvaluation ase = getEvaluator();
   if (ase instanceof OptionHandler) {
     return ase.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler)ase).getOptions());
   }
   return ase.getClass().getName();
 }
 

/**
 * Get the evaluator + options as a string
 *
 * @return a String containing the name of the evalautor + any options
 */
protected String getEvaluatorSpec() {
  AttributeEvaluator a = m_evaluator;
  if (a instanceof OptionHandler) {
    return a.getClass().getName() + " "
      + Utils.joinOptions(((OptionHandler)a).getOptions());
  }
  return a.getClass().getName();
}
 

/**
 * Returns description of the bias-variance decomposition results.
 *
 * @return the bias-variance decomposition results as a string
 */
public String toString() {

    String result = "\nBias-Variance Decomposition Segmentation, Cross Validation\n" +
    "with subsampling.\n";

    if (getClassifier() == null) {
        return "Invalid setup";
    }

    result += "\nClassifier    : " + getClassifier().getClass().getName();
    if (getClassifier() instanceof OptionHandler) {
        result += Utils.joinOptions(((OptionHandler)m_Classifier).getOptions());
    }
    result += "\nData File     : " + getDataFileName();
    result += "\nClass Index   : ";
    if (getClassIndex() == 0) {
        result += "last";
    } else {
        result += getClassIndex();
    }
    result += "\nIterations    : " + getClassifyIterations();
    result += "\np             : " + getP();
    result += "\nTraining Size : " + getTrainSize();
    result += "\nSeed          : " + getSeed();

    result += "\n\nDefinition   : " +"Kohavi and Wolpert";
    result += "\nError         :" + Utils.doubleToString(getError(), 4);
    result += "\nBias^2        :" + Utils.doubleToString(getKWBias(), 4);
    result += "\nVariance      :" + Utils.doubleToString(getKWVariance(), 4);
    result += "\nSigma^2       :" + Utils.doubleToString(getKWSigma(), 4);

    result += "\n\nDefinition   : " +"Webb";
    result += "\nError         :" + Utils.doubleToString(getError(), 4);
    result += "\nBias          :" + Utils.doubleToString(getWBias(), 4);
    result += "\nVariance      :" + Utils.doubleToString(getWVariance(), 4);

    return result;
}
 

/**
 * Constructs a new AssociationRules.
 * 
 * @param rules the list of rules.
 * @param producer the scheme that produced the rules.
 */
public AssociationRules(List<AssociationRule> rules, Object producer) {
  String producerString = producer.getClass().getName();
  if (producerString.startsWith("weka.associations.")) {
    producerString = producerString.substring("weka.associations.".length());
  }    
  
  if (producer instanceof OptionHandler) {
    String [] o = ((OptionHandler) producer).getOptions();
    producerString += " " + Utils.joinOptions(o);
  }
  
  m_rules = rules;
  m_producer = producerString;
}
 

/**
 * Gets the filter specification string, which contains the class name of
 * the filter and any options to the filter.
 *
 * @return 		the filter string.
 */
protected String getFilterSpec() {
  String	result;
  Filter 	filter;
  
  filter = getFilter();
  result = filter.getClass().getName();
  
  if (filter instanceof OptionHandler)
    result += " " + Utils.joinOptions(((OptionHandler) filter).getOptions());
  
  return result;
}
 

/**
 * returns the specification of the given object (class, options if an 
 * instance of OptionHandler)
 *
 * @param o		the object to get the specs as string
 * @return		the specification string
 */
protected String getSpecification(Object o) {
  String      result;

  result = o.getClass().getName();
  if (o instanceof OptionHandler)
    result += " " + Utils.joinOptions(((OptionHandler) o).getOptions());

  return result.trim();
}
 

/**
  * Gets the KDTree specification string, which contains the class name of
  * the KDTree class and any options to the KDTree.
  *
  * @return the KDTree string.
  */
 protected String getKDTreeSpec() {
   
   KDTree c = getKDTree();
   if (c instanceof OptionHandler) {
     return c.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler)c).getOptions());
   }
   return c.getClass().getName();
 }
 

/**
  * Gets the clusterer specification string, which contains the class name of
  * the clusterer and any options to the clusterer.
  *
  * @return the clusterer string.
  */
 protected String getClustererSpec() {
   Clusterer c = getClusterer();
   if (c instanceof OptionHandler) {
     return c.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler)c).getOptions());
   }
   return c.getClass().getName();
 }
 

/**
  * Gets the search specification string, which contains the class name of
  * the search method and any options to it
  *
  * @return the search string.
  */
 protected String getSearchSpec() {
   
   ASSearch s = getSearch();
   if (s instanceof OptionHandler) {
     return s.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler)s).getOptions());
   }
   return s.getClass().getName();
 }