|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD | |||||||||
java.lang.Objectweka.associations.RuleGeneration
weka.associations.CaRuleGeneration
public class CaRuleGeneration
Class implementing the rule generation procedure of the predictive apriori algorithm for class association rules. For association rules in gerneral the method is described in: T. Scheffer (2001). Finding Association Rules That Trade Support Optimally against Confidence. Proc of the 5th European Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'01), pp. 424-435. Freiburg, Germany: Springer-Verlag.
The implementation follows the paper expect for adding a rule to the output of the n best rules. A rule is added if: the expected predictive accuracy of this rule is among the n best and it is not subsumed by a rule with at least the same expected predictive accuracy (out of an unpublished manuscript from T. Scheffer).
| Constructor Summary | |
|---|---|
CaRuleGeneration(ItemSet itemSet)
Constructor |
|
| Method Summary | |
|---|---|
static boolean |
aSubsumesB(RuleItem a,
RuleItem b)
Methods that decides whether or not rule a subsumes rule b. |
java.util.TreeSet |
generateRules(int numRules,
double[] midPoints,
java.util.Hashtable priors,
double expectation,
Instances instances,
java.util.TreeSet best,
int genTime)
Generates all rules for an item set. |
java.lang.String |
getRevision()
Returns the revision string. |
static FastVector |
singleConsequence(Instances instances)
generates a consequence of length 1 for a class association rule. |
static FastVector |
singletons(Instances instances)
Converts the header info of the given set of instances into a set of item sets (singletons). |
| Methods inherited from class weka.associations.RuleGeneration |
|---|
binomialDistribution, change, count, expectation, removeRedundant, singleConsequence |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public CaRuleGeneration(ItemSet itemSet)
itemSet - the item set that forms the premise of the rule| Method Detail |
|---|
public java.util.TreeSet generateRules(int numRules,
double[] midPoints,
java.util.Hashtable priors,
double expectation,
Instances instances,
java.util.TreeSet best,
int genTime)
generateRules in class RuleGenerationnumRules - the number of association rules the use wants to mine.
This number equals the size n of the list of the
best rules.midPoints - the mid points of the intervalspriors - Hashtable that contains the prior probabilitiesexpectation - the minimum value of the expected predictive accuracy
that is needed to get into the list of the best rulesinstances - the instances for which association rules are generatedbest - the list of the n best rules.
The list is implemented as a TreeSetgenTime - the maximum time of generation
public static boolean aSubsumesB(RuleItem a,
RuleItem b)
a - an association rule stored as a RuleItemb - an association rule stored as a RuleItem
public static FastVector singletons(Instances instances)
throws java.lang.Exception
instances - the set of instances whose header info is to be used
java.lang.Exception - if singletons can't be generated successfullypublic static FastVector singleConsequence(Instances instances)
instances - the instances under consideration
public java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class RuleGeneration
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD | |||||||||