A B C E F G L M N P R S T U W

A

accuracy() - Method in class weka.associations.RuleItem
Gets the expected predictive accuracy of a rule
addCons(int[]) - Method in class weka.associations.PriorEstimation
generates a class association rule out of a given premise.
aSubsumesB(RuleItem, RuleItem) - Static method in class weka.associations.CaRuleGeneration
Methods that decides whether or not rule a subsumes rule b.
aSubsumesB(RuleItem, RuleItem) - Static method in class weka.associations.RuleGeneration
Methods that decides whether or not rule a subsumes rule b.

B

binomialDistribution(double, double, double) - Static method in class weka.associations.RuleGeneration
calculates the probability using a binomial distribution.
buildAssociations(Instances) - Method in class weka.associations.PredictiveApriori
Method that generates all large itemsets with a minimum support, and from these all association rules.
buildDistribution(double, double) - Method in class weka.associations.PriorEstimation
updates the distribution of the confidence values.

C

calculatePriorSum(boolean, double) - Method in class weka.associations.PriorEstimation
calculates the numerator and the denominator of the prior equation
carTipText() - Method in class weka.associations.PredictiveApriori
Returns the tip text for this property
CaRuleGeneration - Class in weka.associations
Class implementing the rule generation procedure of the predictive apriori algorithm for class association rules.
CaRuleGeneration(ItemSet) - Constructor for class weka.associations.CaRuleGeneration
Constructor
change() - Method in class weka.associations.RuleGeneration
Gets if the list fo the best rules has been changed
classIndexTipText() - Method in class weka.associations.PredictiveApriori
Returns the tip text for this property
compareTo(Object) - Method in class weka.associations.RuleItem
compares two RuleItems and allows an ordering concerning expected predictive accuracy and time of generation Note: this class has a natural ordering that is inconsistent with equals
consequence() - Method in class weka.associations.RuleItem
Gets the consequence of a rule
count() - Method in class weka.associations.RuleGeneration
Gets the actual maximum value of the generation time

E

equals(Object) - Method in class weka.associations.RuleItem
returns whether two RuleItems are equal
estimatePrior() - Method in class weka.associations.PriorEstimation
Method to estimate the prior probabilities
expectation(double, int, double[], Hashtable) - Static method in class weka.associations.RuleGeneration
calculates the expected predctive accuracy of a rule

F

findIntervall(double) - Method in class weka.associations.PriorEstimation
searches the mid point of the interval a given confidence value falls into

G

generateDistribution() - Method in class weka.associations.PriorEstimation
Calculates the prior distribution.
generateRuleItem(ItemSet, ItemSet, Instances, int, int, double[], Hashtable) - Method in class weka.associations.RuleItem
Constructs a new RuleItem if the support of the given rule is above the support threshold.
generateRules(int, double[], Hashtable, double, Instances, TreeSet, int) - Method in class weka.associations.CaRuleGeneration
Generates all rules for an item set.
generateRules(int, double[], Hashtable, double, Instances, TreeSet, int) - Method in class weka.associations.RuleGeneration
Generates all rules for an item set.
getAllTheRules() - Method in class weka.associations.PredictiveApriori
returns all the rules
getCapabilities() - Method in class weka.associations.PredictiveApriori
Returns default capabilities of the classifier.
getCar() - Method in class weka.associations.PredictiveApriori
Gets whether class association ruels are mined
getClassIndex() - Method in class weka.associations.PredictiveApriori
Gets the index of the class attribute
getInstancesNoClass() - Method in class weka.associations.PredictiveApriori
Gets the instances without the class attribute
getInstancesOnlyClass() - Method in class weka.associations.PredictiveApriori
Gets the class attribute of all instances
getMidPoints() - Method in class weka.associations.PriorEstimation
returns an ordered array of all mid points
getNumRules() - Method in class weka.associations.PredictiveApriori
Get the value of the number of required rules.
getOptions() - Method in class weka.associations.PredictiveApriori
Gets the current settings of the PredictiveApriori object.
getRevision() - Method in class weka.associations.CaRuleGeneration
Returns the revision string.
getRevision() - Method in class weka.associations.PredictiveApriori
Returns the revision string.
getRevision() - Method in class weka.associations.PriorEstimation
Returns the revision string.
getRevision() - Method in class weka.associations.RuleGeneration
Returns the revision string.
getRevision() - Method in class weka.associations.RuleItem
Returns the revision string.
getTechnicalInformation() - Method in class weka.associations.PredictiveApriori
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
globalInfo() - Method in class weka.associations.PredictiveApriori
Returns a string describing this associator

L

listOptions() - Method in class weka.associations.PredictiveApriori
Returns an enumeration describing the available options.
logbinomialCoefficient(int, int) - Static method in class weka.associations.PriorEstimation
Method that calculates the base 2 logarithm of a binomial coefficient

M

main(String[]) - Static method in class weka.associations.PredictiveApriori
Main method.
metricString() - Method in class weka.associations.PredictiveApriori
Returns the metric string for the chosen metric type.
midPoint(double, int) - Method in class weka.associations.PriorEstimation
calculates the mid point of an interval
midPoints() - Method in class weka.associations.PriorEstimation
split the interval [0,1] into a predefined number of intervals and calculates their mid points
mineCARs(Instances) - Method in class weka.associations.PredictiveApriori
Method that mines the n best class association rules.

N

numRulesTipText() - Method in class weka.associations.PredictiveApriori
Returns the tip text for this property

P

PredictiveApriori - Class in weka.associations
Class implementing the predictive apriori algorithm to mine association rules.
It searches with an increasing support threshold for the best 'n' rules concerning a support-based corrected confidence value.

For more information see:

Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence.
PredictiveApriori() - Constructor for class weka.associations.PredictiveApriori
Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
premise() - Method in class weka.associations.RuleItem
Gets the premise of a rule
PriorEstimation - Class in weka.associations
Class implementing the prior estimattion of the predictive apriori algorithm for mining association rules.
PriorEstimation(Instances, int, int, boolean) - Constructor for class weka.associations.PriorEstimation
Constructor

R

randomCARule(int, int, Random) - Method in class weka.associations.PriorEstimation
Constructs an item set of certain length randomly.
randomRule(int, int, Random) - Method in class weka.associations.PriorEstimation
Constructs an item set of certain length randomly.
removeRedundant(RuleItem) - Method in class weka.associations.RuleGeneration
Method that removes redundant rules out of the list of the best rules.
resetOptions() - Method in class weka.associations.PredictiveApriori
Resets the options to the default values.
RuleGeneration - Class in weka.associations
Class implementing the rule generation procedure of the predictive apriori algorithm.
RuleGeneration(ItemSet) - Constructor for class weka.associations.RuleGeneration
Constructor
RuleItem - Class in weka.associations
Class for storing an (class) association rule.
RuleItem() - Constructor for class weka.associations.RuleItem
Constructor for an empty RuleItem
RuleItem(RuleItem) - Constructor for class weka.associations.RuleItem
Constructor that generates a RuleItem out of a given one
RuleItem(ItemSet, ItemSet, int, int, double[], Hashtable) - Constructor for class weka.associations.RuleItem
Constructor

S

setCar(boolean) - Method in class weka.associations.PredictiveApriori
Sets class association rule mining
setClassIndex(int) - Method in class weka.associations.PredictiveApriori
Sets the class index
setNumRules(int) - Method in class weka.associations.PredictiveApriori
Set the value of required rules.
setOptions(String[]) - Method in class weka.associations.PredictiveApriori
Parses a given list of options.
singleConsequence(Instances) - Static method in class weka.associations.CaRuleGeneration
generates a consequence of length 1 for a class association rule.
singleConsequence(Instances, int, FastVector) - Static method in class weka.associations.RuleGeneration
generates a consequence of length 1 for an association rule.
singletons(Instances) - Static method in class weka.associations.CaRuleGeneration
Converts the header info of the given set of instances into a set of item sets (singletons).
splitItemSet(int, int[]) - Method in class weka.associations.PriorEstimation
splits an item set into premise and consequence and constructs therefore an association rule.

T

toString() - Method in class weka.associations.PredictiveApriori
Outputs the association rules.

U

updateCounters(ItemSet) - Method in class weka.associations.PriorEstimation
updates the support count of an item set

W

weka.associations - package weka.associations
 

A B C E F G L M N P R S T U W