Serialized Form


Package wpi.associations

Class wpi.associations.AprioriSets extends Associator implements Serializable

Serialized Fields

m_minSupport

double m_minSupport
The minimum support.


m_upperBoundMinSupport

double m_upperBoundMinSupport
The upper bound on the support


m_lowerBoundMinSupport

double m_lowerBoundMinSupport
The lower bound for the minimum support.


m_minConfidence

double m_minConfidence
The minimum confidence score.


m_maxRulesOutput

int m_maxRulesOutput
The maximum number of rules that are output.


m_verbose

boolean m_verbose
Verbose mode?


m_delta

double m_delta
Delta by which m_minSupport is decreased in each iteration.


m_cycles

int m_cycles
Number of cycles used before required number of rules was one.


m_Ls

weka.core.FastVector m_Ls
The set of all sets of itemsets L.


m_hashtables

weka.core.FastVector m_hashtables
The same information stored in hash tables.


m_allTheRules

weka.core.FastVector[] m_allTheRules
The list of all generated rules.


m_instances

weka.core.Instances m_instances
The instances (transactions) to be used for generating the association rules.


m_outputItemSets

boolean m_outputItemSets
Output itemsets found?


m_maxAntecedents

int m_maxAntecedents
The maximum number of antecedents in a rule


m_minConsequents

int m_minConsequents
The minimum number of consequents in a rule


m_rulesFound

java.util.Vector m_rulesFound
The vector containing all found AssociationRules


m_requiredAntecedentAttributes

weka.core.Range m_requiredAntecedentAttributes
The attributes required to be in the antecedents of the rules


m_requiredConsequentAttributes

weka.core.Range m_requiredConsequentAttributes
The attributes required to be in the consequents of the rules


m_attributeHash

java.util.Hashtable m_attributeHash
A hash listing attribute value pair Strings by Integer key

Class wpi.associations.AprioriSetsAndSequences extends Associator implements Serializable

Serialized Fields

m_minSupport

double m_minSupport
The minimum support.


m_upperBoundMinSupport

double m_upperBoundMinSupport
The upper bound on the support


m_lowerBoundMinSupport

double m_lowerBoundMinSupport
The lower bound for the minimum support.


m_minConfidence

double m_minConfidence
The minimum confidence score.


m_maxRulesOutput

int m_maxRulesOutput
The maximum number of rules that are output.


m_delta

double m_delta
Delta by which m_minSupport is decreased in each iteration.


m_cycles

int m_cycles
Number of cycles used before required number of rules was one.


m_instances

weka.core.Instances m_instances
The instances (transactions) to be used for generating the association rules.


m_minAntecedent

int m_minAntecedent
The minimum number of antecedents in a rule


m_maxAntecedent

int m_maxAntecedent
The maximum number of antecedents in a rule


m_minConsequent

int m_minConsequent
The minimum number of consequents in a rule


m_maxConsequent

int m_maxConsequent
The maximum number of consequents in a rule


maxEvents

int maxEvents
The maximum number of events of the same kind allowed in a rule.


m_rulesFound

java.util.Vector m_rulesFound
The vector containing all found AssociationRules


m_requiredAntecedentAttributes

weka.core.Range m_requiredAntecedentAttributes
The attributes required to be in the antecedents of the rules


m_requiredConsequentAttributes

weka.core.Range m_requiredConsequentAttributes
The attributes required to be in the consequents of the rules


m_attributeHash

java.util.Hashtable m_attributeHash
A hash listing attribute value pair Strings by Integer key


cacheFileName

java.lang.String cacheFileName
File name to load cached frequent itemsets from


logStats

boolean logStats
Specifies statistics should be written to a log file.

Class wpi.associations.Associator extends weka.associations.Associator implements Serializable

Serialized Fields

logger

Logger logger
The object responsible for logging.


logStatsFileName

java.lang.String logStatsFileName
The name of the log file to write to.


Package wpi.associations.arminer

Class wpi.associations.arminer.ARMinerItemset extends java.lang.Object implements Serializable

Serialized Fields

capacity

int capacity
The capacity of the itemset.

 

size

int size
The number of items in the itemset.

 

set

int[] set
The itemset.

 

support

float support
The support of the itemset.

 

weight

long weight
The weight of the itemset.

 

mark

boolean mark
The mark of the itemset.

 

index

int index
Internal index used for cycling through the itemset's items.

 

sum

int sum

Class wpi.associations.arminer.AssociationRule extends java.lang.Object implements Serializable

Serialized Fields

antecedent

int[] antecedent
The antecedent.

 

consequent

int[] consequent
The consequent.

 

support

float support
The support of the association rule.

 

confidence

float confidence
The confidence of the association rule.

 

Class wpi.associations.arminer.DBException extends java.lang.Exception implements Serializable

Class wpi.associations.arminer.SETException extends java.lang.Exception implements Serializable

Serialized Fields

text

java.lang.String text
 


Package wpi.associations.arminerSequence

Class wpi.associations.arminerSequence.ARMinerItemset extends java.lang.Object implements Serializable

Serialized Fields

capacity

int capacity
The capacity of the item set. @serial


size

int size
The number of items in the item set. @serial


set

int[] set
The item set. @serial


support

float support
The support of the item set. @serial


weight

long weight
The weight of the item set. @serial


mark

boolean mark
The mark of the item set. This can be used to mark the item set for various purposes. @serial


iterateIndex

int iterateIndex
Internal index used for cycling through the item set's items. @serial


sum

int sum

eventWeight

long eventWeight
The weight of the item set's events. @serial


numberHash

java.util.Hashtable numberHash
Used to look up actual value of an item using its integer representation.


nameHash

java.util.Hashtable nameHash
The name of time sequence event attributes


realHash

java.util.Hashtable realHash
Used to look up the real begin and end times of the events in this item set.


relativeHash

java.util.Hashtable relativeHash
Used to look up the relative begin and end times of the events in this item set.


relativeVector

java.util.Vector relativeVector
The relative time labels and corresponding real time values


eventVector

java.util.Vector eventVector
A vector of vectors. Each vector contains a list of the time sequence event item labels corresponding to the relative time as denoted by eventVector's index. Used for relabeling when changes occur.

Class wpi.associations.arminerSequence.AssociationRule extends java.lang.Object implements Serializable

Serialized Fields

antecedent

int[] antecedent
The antecedent. @serial


consequent

int[] consequent
The consequent. @serial


support

float support
The support of the association rule. @serial


antecedentSupport

float antecedentSupport
The support of the antecedent of association rule. @serial


consequentSupport

float consequentSupport
The support of the consequent of association rule. @serial


antecedentEventWeight

float antecedentEventWeight
The event weight of the antecedent of association rule. @serial


consequentEventWeight

float consequentEventWeight
The event weight of the consequent of association rule. @serial


ruleEventWeight

float ruleEventWeight
The event weight of the association rule. This is the number of times the consequent is found to match a previously found antecedent. @serial


confidence

float confidence
The confidence of the association rule. @serial


numInstances

int numInstances
Number of instances in the data set. Used for computing statistical measures


originalItemset

ARMinerItemset originalItemset
the original item set the rule's antecedent and consequent were derived from

Class wpi.associations.arminerSequence.DBException extends java.lang.Exception implements Serializable

Class wpi.associations.arminerSequence.SETException extends java.lang.Exception implements Serializable

Serialized Fields

text

java.lang.String text
 


Package wpi.filters

Class wpi.filters.AddWithValueFilter extends weka.filters.AddFilter implements Serializable

Serialized Fields

value

java.lang.String value
The value to assign

Class wpi.filters.AttributeSetFilter extends weka.filters.Filter implements Serializable

Serialized Fields

m_nom_values

int m_nom_values
The integer defining current nominal values.


SET

java.lang.String SET
The string definining a set.


NONSET

java.lang.String NONSET
The string defining a non-set.


m_InputFormat

weka.core.Instances m_InputFormat
Stores the input format.


m_OutputFormat

weka.core.Instances m_OutputFormat
Stores the output format.


m_SetFormat

weka.core.FastVector m_SetFormat
Stores the set format.
e.g. [SET][entry][entry][entry][NONSET][SET][entry]


m_nom_yes

java.lang.String m_nom_yes
Stores the nominal value for an instance with an entry.


m_nom_no

java.lang.String m_nom_no
Stores the nominal value for an instance without an entry.


m_delimiters

java.lang.String m_delimiters
Stores the delimeter(s) used for separating entries in a set.


m_range

java.lang.String m_range
Stores the range of filtering as a string.


m_rangeInverse

boolean m_rangeInverse
Stores whether the range of filtering should be inversed, or not.


m_hashCapacity

int m_hashCapacity
Stores the initial hash capacity for a hash used internally.

Class wpi.filters.EventFilter extends weka.filters.Filter implements Serializable

Serialized Fields

timeSequenceAttributeVector

java.util.Vector timeSequenceAttributeVector
list of time sequence attributes to find events in


attributeString

java.lang.String attributeString
The original string for attributes to look for events in


tolerance

double tolerance
tolerance for events


minNumValues

int minNumValues
minimum required number of values for events


increaseEvents

boolean increaseEvents
find increase events?


decreaseEvents

boolean decreaseEvents
find decrease events?


sustainEvents

boolean sustainEvents
find sustain events?

Class wpi.filters.TimeGranularityFilter extends weka.filters.Filter implements Serializable

Serialized Fields

maxTime

double maxTime
For the numbered granularities we need to know the maximum time noted in the dataset.


eventAttributeVector

java.util.Vector eventAttributeVector
list of time sequence attributes to find events in


numberedGranularities

boolean numberedGranularities
numbered option


halfGranularity

boolean halfGranularity
create half granularity?


userGranularitySize

int userGranularitySize
size of user defined granularity


numberedUserAttributeStringArray

java.lang.String[] numberedUserAttributeStringArray
names for the attributes of the user numbered granularities

Class wpi.filters.TimeSequenceInstanceFilter extends weka.filters.Filter implements Serializable