Serialized Form
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
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.
logger
Logger logger
- The object responsible for logging.
logStatsFileName
java.lang.String logStatsFileName
- The name of the log file to write to.
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Package wpi.associations.arminer |
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
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.
-
text
java.lang.String text
-
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Package wpi.associations.arminerSequence |
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.
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
text
java.lang.String text
-
value
java.lang.String value
- The value to assign
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.
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?
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