Author |
Boris Capitanu |
Creation date |
06/01/2011 |
Firing policy |
all |
Package |
org.seasr.meandre.components.discovery.ruleassociation |
DESCRIPTION
This module works in conjunction with other modules implementing the Apriori rule association algorithm to generate association rules satisfying a minimum confidence threshold.
Detailed Description: This module takes as input an Item Sets object generated by the Table To Item Sets module, and Frequent Itemsets generated by the Apriori or FPGrowth module. From these inputs, it develops a set of possible association rules, each with a single target item, where an item consists of an [attribute,value] pair. For each possible rule, this module computes the Confidence in the prediction, and accepts those rules that meet a minimum confidence threshold specified via the property editor.
For a rule of the form Antecedent A implies Consequent C, the Confidence is the percentage of examples in the original data that contain A that also contain C. The formula to compute the confidence of the rule A->C is:
Confidence = ( (# of examples with A and C) / (# of examples with A ) ) * 100.00
Limitations: The Apriori, FPGrowthand Compute Confidence modules currently build rules with a single item in the consequent.
Scalability: This module searches all the Items Sets to compute the confidence for each Frequent Itemset. The module allocated memory for the resulting Rule Table.
INPUTS
Name |
Description |
Example |
|---|---|---|
freq_item_sets |
The frequent itemsets found by an Apriori module. These are the item combinations that frequently appear together in the original examples. |
|
item_sets |
An Item Sets object containing the items of interest in the original data. This object is typically produced by a Table To Item Sets module. |
|
OUTPUTS
Name |
Description |
Example |
|---|---|---|
error |
This port is used to output any unhandled errors encountered during the execution of this component |
|
rule_table |
A representation of the association rules found and accepted by this module. This output is typically connected to a Rule Visualization module. |
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PROPERTIES
Name |
Description |
Default value |
|---|---|---|
verbose |
If this property is true, the module will report progress information to the console. |
False |
_debug_level |
Controls the verbosity of debug messages printed by the component during execution. Possible values are: off, severe, warning, info, config, fine, finer, finest, all Append ',mirror' to any of the values above to mirror that output to the server logs. |
info |
confidence |
The percent of the examples containing a rule antecedent that must also contain the rule consequent before a potential association rule is accepted. This value must be greater than 0 and less than or equal to 100. |
70.0 |
_ignore_errors |
Set to 'true' to ignore all unhandled exceptions and prevent the flow from being terminated. Setting this property to 'false' will result in the flow being terminated in the event an unhandled exception is thrown during the execution of this component |
false |
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