Documentation Index

Fetch the complete documentation index at: https://docs.darwinium.com/llms.txt

Use this file to discover all available pages before exploring further.

Statistic Of Expression

Prev Next

The Statistic Of Expression Feature calculates one or more statistics on the result of a mathematic expression that is calculated against past events. The mathematic expression can include Subject attributes that are numeric or integer. Each statistic is output to a Feature with its own name.

For Example:

  • The average (string) length of auction listing description
  • The average and minimum (string) length of a payment reference

Configuration

  • Feature Name
    The "dictionary" name under which the feature value will be stored.

  • Expression
    A Query-Language expression that will be evaluated against past events.

Note
  • The expression should result in a numeric value.
  • Into Features
    • Time Between can calculate multiple statistics from a single configuration and output them to the Feature Names given. Simply fill in the Feature Name for the required statistics, any that are not required can be left blank.
Note
  • There are multiple Feature Names generated, a Feature Name must be given to each of the required statistics.
Optional Configuration
  • Default Value
    A value that can be assigned to the feature if the attributes to calculate the features are not present.
  • Scope
    Can be used to extend the event search from the local node, to all nodes within the same organization all the way to all across customers (global).
  • For Events
    Provides a way of filtering past events based on their type.
  • Condition
    A Query-Language filter that can be used to refine Features for specific use cases.
  • Time Window
    Can be used to limit the Feature calculation to a specific time period/window. e.g 1 week.
  • Starting ...
    Can be used to remove recent events from Feature calculation.

Use Case 1

The average (string) length of auction listing description. New auction listings could then be checked to see if they are less than half the average length for a user over the last 3 months to detect anomolous behaviour:

len(auction_lising.description) < (outcome['CHAMPION'].features.general['avg_description_len_3mths'] * 0.5)

Implementing In The Feature Editor

image.png

image.png

image.png

image.png