The Associations mining function finds items in your data
that frequently occur together in the same transactions.
Concepts
You can use the Associations mining function to find association
rules among items that are present in a set of groups.
Items and groups
When you define associations mining settings, you specify
items and groups.
Rule body and rule head
The principal parts of an association rule are the rule
body (also referred to as antecedent) and the rule head (also
referred to as consequent).
Support in an association rule
The support of an association rule is the percentage
of groups that contain all of the items listed in that association
rule. The percentage value is calculated from among all the groups
that were considered. This percentage value shows how often the joined rule
body and rule head occur among all of the groups that were considered.
Confidence in an association rule
The confidence of an association rule is a percentage
value that shows how frequently the rule head occurs among all the
groups containing the rule body. The confidence value indicates how
reliable this rule is. The higher the value, the more likely the head
items occur in a group if it is known that all body items are contained
in that group.
Lift in an association rule
The lift value is a measure of importance of a rule. By
using rule filters, you can define the desired lift range in the settings.
Name mappings
A name mapping maps a field value in the physical data
to another more meaningful name.
Taxonomies
You can make the associations or the sequences that are
found among items more meaningful if you group the items in categories.
You can group these categories again into subcategories. The result
is a hierarchy of categories with the items on the lowest level. This
is called a taxonomy.
Rule filtering
You can control the nature or the number of rules that
are found by the Associations mining function by using rule filters.
Rule filters are a powerful way to limit the amount of rules to be
generated or the content of the rules.
Active or inactive fields
You can split the input fields into active or inactive fields.
Active fields are used to build a model. Inactive field are ignored
when the model is built.