sequencenode properties
The Sequence node discovers association rules in sequential or time-oriented
data. A sequence is a list of item sets that tends to occur in a predictable order. For example, a
customer who purchases a razor and aftershave lotion may purchase shaving cream the next time he
shops. The Sequence node is based on the CARMA association rules algorithm, which uses an efficient
two-pass method for finding sequences.
Example
node = stream.create("sequence", "My node")
# "Fields" tab
node.setPropertyValue("id_field", "Age")
node.setPropertyValue("contiguous", True)
node.setPropertyValue("use_time_field", True)
node.setPropertyValue("time_field", "Date1")
node.setPropertyValue("content_fields", ["Drug", "BP"])
node.setPropertyValue("partition", "Test")
# "Model" tab
node.setPropertyValue("use_model_name", True)
node.setPropertyValue("model_name", "Sequence_test")
node.setPropertyValue("use_partitioned_data", False)
node.setPropertyValue("min_supp", 15.0)
node.setPropertyValue("min_conf", 14.0)
node.setPropertyValue("max_size", 7)
node.setPropertyValue("max_predictions", 5)
# "Expert" tab
node.setPropertyValue("mode", "Expert")
node.setPropertyValue("use_max_duration", True)
node.setPropertyValue("max_duration", 3.0)
node.setPropertyValue("use_pruning", True)
node.setPropertyValue("pruning_value", 4.0)
node.setPropertyValue("set_mem_sequences", True)
node.setPropertyValue("mem_sequences", 5.0)
node.setPropertyValue("use_gaps", True)
node.setPropertyValue("min_item_gap", 20.0)
node.setPropertyValue("max_item_gap", 30.0)
sequencenode Properties |
Values | Property description |
|---|---|---|
id_field
|
field | To create a Sequence model, you need to specify an ID field, an optional time field, and one or more content fields. Weight and frequency fields are not used. See Common modeling node properties for more information. |
time_field
|
field | |
use_time_field
|
flag | |
content_fields
|
[field1 ... fieldn] | |
contiguous
|
flag | |
min_supp
|
number | |
min_conf
|
number | |
max_size
|
number | |
max_predictions
|
number | |
mode
|
Simple
Expert
|
|
use_max_duration
|
flag | |
max_duration
|
number | |
use_gaps
|
flag | |
min_item_gap
|
number | |
max_item_gap
|
number | |
use_pruning
|
flag | |
pruning_value
|
number | |
set_mem_sequences
|
flag | |
mem_sequences
|
integer |