This is the cl-association-rules Reference Manual, version 0.0.1, generated automatically by Declt version 4.0 beta 2 "William Riker" on Sun Dec 08 16:43:09 2024 GMT+0.
The main system appears first, followed by any subsystem dependency.
cl-association-rules
An implementation of the apriori algorithm to mine association rules in Common Lisp.
Diogo Franco
MIT
0.0.1
package.lisp
(file).
rule.lisp
(file).
apriori.lisp
(file).
Files are sorted by type and then listed depth-first from the systems components trees.
cl-association-rules/cl-association-rules.asd
cl-association-rules/package.lisp
cl-association-rules/rule.lisp
cl-association-rules/apriori.lisp
cl-association-rules/cl-association-rules.asd
cl-association-rules
(system).
cl-association-rules/package.lisp
cl-association-rules
(system).
cl-association-rules/rule.lisp
package.lisp
(file).
cl-association-rules
(system).
make-rule
(function).
print-object
(method).
rule-confidence
(reader).
(setf rule-confidence)
(writer).
rule-posttuple
(reader).
(setf rule-posttuple)
(writer).
rule-pretuple
(reader).
(setf rule-pretuple)
(writer).
rule-support
(reader).
(setf rule-support)
(writer).
cl-association-rules/apriori.lisp
rule.lisp
(file).
cl-association-rules
(system).
apriori
(function).
generate-candidates
(function).
generate-rules
(function).
get-all-items
(function).
get-frequent-items
(function).
set-equal-p
(function).
Packages are listed by definition order.
cl-association-rules
rules
common-lisp
.
apriori
(function).
make-rule
(function).
rule-confidence
(reader).
(setf rule-confidence)
(writer).
rule-posttuple
(reader).
(setf rule-posttuple)
(writer).
rule-pretuple
(reader).
(setf rule-pretuple)
(writer).
rule-support
(reader).
(setf rule-support)
(writer).
copy-rule
(function).
generate-candidates
(function).
generate-rules
(function).
get-all-items
(function).
get-frequent-items
(function).
rule
(structure).
rule-p
(function).
set-equal-p
(function).
Definitions are sorted by export status, category, package, and then by lexicographic order.
Calculates the association rules in the dataset using the apriori
algorithm. Expects a dataset of the form
((1 2 3 4)
(3 2 7 9)
(9)
(2 3 8)
(2 0)),
where each line is a transaction.
Returns a list of the mined rules.
Generates the next candidate set, from the previous frequent and non-frequent itemsets.
From the frequent itemsets found by apriori, generate association rules for a given min-confidence.
From a dataset, return the unique items as a list.
From a candidate set and support threshold, return the items that are frequent and non-frequent in the dataset.
Returns t if two sets of elements are equal
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