decisionlistnode properties

Decision List node iconThe Decision List node identifies subgroups, or segments, that show a higher or lower likelihood of a given binary outcome relative to the overall population. For example, you might look for customers who are unlikely to churn or are most likely to respond favorably to a campaign. You can incorporate your business knowledge into the model by adding your own custom segments and previewing alternative models side by side to compare the results. Decision List models consist of a list of rules in which each rule has a condition and an outcome. Rules are applied in order, and the first rule that matches determines the outcome.


node = stream.create("decisionlist", "My node")
node.setPropertyValue("search_direction", "Down")
node.setPropertyValue("target_value", 1)
node.setPropertyValue("max_rules", 4)
node.setPropertyValue("min_group_size_pct", 15)
Table 1. decisionlistnode properties
decisionlistnode Properties Values Property description
target field Decision List models use a single target and one or more input fields. A frequency field can also be specified. See Common modeling node properties for more information.
model_output_type Model InteractiveBuilder  
search_direction Up Down Relates to finding segments; where Up is the equivalent of High Probability, and Down is the equivalent of Low Probability.
target_value string If not specified, will assume true value for flags.
max_rules integer The maximum number of segments excluding the remainder.
min_group_size integer Minimum segment size.
min_group_size_pct number Minimum segment size as a percentage.
confidence_level number Minimum threshold that an input field has to improve the likelihood of response (give lift), to make it worth adding to a segment definition.
max_segments_per_rule integer  
mode Simple Expert  
bin_method EqualWidth EqualCount  
bin_count number  
max_models_per_cycle integer Search width for lists.
max_rules_per_cycle integer Search width for segment rules.
segment_growth number  
include_missing flag  
final_results_only flag  
reuse_fields flag Allows attributes (input fields which appear in rules) to be re-used.
max_alternatives integer  
calculate_raw_propensities flag  
calculate_adjusted_propensities flag  
adjusted_propensity_partition Test Validation