?? cls.java
字號:
}
}
/**
* Gets the current settings of the Classifier.
*
* @return an array of strings suitable for passing to setOptions
*/
public String [] getOptions() {
String [] options = new String [10];
int current = 0;
if (m_noCleanup) {
options[current++] = "-L";
}
if (m_unpruned) {
options[current++] = "-U";
} else {
if (!m_subtreeRaising) {
options[current++] = "-S";
}
if (m_reducedErrorPruning) {
options[current++] = "-R";
options[current++] = "-N"; options[current++] = "" + m_numFolds;
} else {
options[current++] = "-C"; options[current++] = "" + m_CF;
}
}
if (m_binarySplits) {
options[current++] = "-B";
}
options[current++] = "-M"; options[current++] = "" + m_minNumObj;
if (m_useLaplace) {
options[current++] = "-A";
}
while (current < options.length) {
options[current++] = "";
}
return options;
}
/**
* Get the value of useLaplace.
*
* @return Value of useLaplace.
*/
public boolean getUseLaplace() {
return m_useLaplace;
}
/**
* Set the value of useLaplace.
*
* @param newuseLaplace Value to assign to useLaplace.
*/
public void setUseLaplace(boolean newuseLaplace) {
m_useLaplace = newuseLaplace;
}
/**
* Returns a description of the classifier.
*/
public String toString() {
if (m_root == null) {
return "No classifier built";
}
if (m_unpruned)
return "CLS unpruned tree\n------------------\n" + m_root.toString();
else
// System.out.println("Takis");
return "CLS pruned tree\n------------------\n" + m_root.toString();
}
/**
* Returns a superconcise version of the model
*/
public String toSummaryString() {
return "Number of leaves: " + m_root.numLeaves() + "\n"
+ "Size of the tree: " + m_root.numNodes() + "\n";
}
/**
* Returns the size of the tree
* @return the size of the tree
*/
public double measureTreeSize() {
return m_root.numNodes();
}
/**
* Returns the number of leaves
* @return the number of leaves
*/
public double measureNumLeaves() {
return m_root.numLeaves();
}
/**
* Returns the number of rules (same as number of leaves)
* @return the number of rules
*/
public double measureNumRules() {
return m_root.numLeaves();
}
/**
* Returns an enumeration of the additional measure names
* @return an enumeration of the measure names
*/
public Enumeration enumerateMeasures() {
Vector newVector = new Vector(3);
newVector.addElement("measureTreeSize");
newVector.addElement("measureNumLeaves");
newVector.addElement("measureNumRules");
return newVector.elements();
}
/**
* Returns the value of the named measure
* @param measureName the name of the measure to query for its value
* @return the value of the named measure
* @exception IllegalArgumentException if the named measure is not supported
*/
public double getMeasure(String additionalMeasureName) {
if (additionalMeasureName.compareTo("measureNumRules") == 0) {
return measureNumRules();
} else if (additionalMeasureName.compareTo("measureTreeSize") == 0) {
return measureTreeSize();
} else if (additionalMeasureName.compareTo("measureNumLeaves") == 0) {
return measureNumLeaves();
} else {
throw new IllegalArgumentException(additionalMeasureName
+ " not supported (cls)");
}
}
/**
* Get the value of unpruned.
*
* @return Value of unpruned.
*/
public boolean getUnpruned() {
return m_unpruned;
}
/**
* Set the value of unpruned. Turns reduced-error pruning
* off if set.
* @param v Value to assign to unpruned.
*/
public void setUnpruned(boolean v) {
if (v) {
m_reducedErrorPruning = false;
}
m_unpruned = v;
}
/**
* Get the value of CF.
*
* @return Value of CF.
*/
public float getConfidenceFactor() {
return m_CF;
}
/**
* Set the value of CF.
*
* @param v Value to assign to CF.
*/
public void setConfidenceFactor(float v) {
m_CF = v;
}
/**
* Get the value of minNumObj.
*
* @return Value of minNumObj.
*/
public int getMinNumObj() {
return m_minNumObj;
}
/**
* Set the value of minNumObj.
*
* @param v Value to assign to minNumObj.
*/
public void setMinNumObj(int v) {
m_minNumObj = v;
}
/**
* Get the value of reducedErrorPruning.
*
* @return Value of reducedErrorPruning.
*/
public boolean getReducedErrorPruning() {
return m_reducedErrorPruning;
}
/**
* Set the value of reducedErrorPruning. Turns
* unpruned trees off if set.
*
* @param v Value to assign to reducedErrorPruning.
*/
public void setReducedErrorPruning(boolean v) {
if (v) {
m_unpruned = false;
}
m_reducedErrorPruning = v;
}
/**
* Get the value of numFolds.
*
* @return Value of numFolds.
*/
public int getNumFolds() {
return m_numFolds;
}
/**
* Set the value of numFolds.
*
* @param v Value to assign to numFolds.
*/
public void setNumFolds(int v) {
m_numFolds = v;
}
/**
* Get the value of binarySplits.
*
* @return Value of binarySplits.
*/
public boolean getBinarySplits() {
return m_binarySplits;
}
/**
* Set the value of binarySplits.
*
* @param v Value to assign to binarySplits.
*/
public void setBinarySplits(boolean v) {
m_binarySplits = v;
}
/**
* Get the value of subtreeRaising.
*
* @return Value of subtreeRaising.
*/
public boolean getSubtreeRaising() {
return m_subtreeRaising;
}
/**
* Set the value of subtreeRaising.
*
* @param v Value to assign to subtreeRaising.
*/
public void setSubtreeRaising(boolean v) {
m_subtreeRaising = v;
}
/**
* Check whether instance data is to be saved.
*
* @return true if instance data is saved
*/
public boolean getSaveInstanceData() {
return m_noCleanup;
}
/**
* Set whether instance data is to be saved.
* @param v true if instance data is to be saved
*/
public void setSaveInstanceData(boolean v) {
m_noCleanup = v;
}
//private ClassifierTree m_root;
public ClassifierTree getClassifierTree() {
return m_root;
}
/**
* Main method for testing this class
*
* @param String options
*/
/* public static void main (String [] args){
try{
System.out.println(Evaluation.evaluateModel(new J48(), args));
}
catch (Exception e){
System.out.println(e);
}
}
*/
}
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