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basket plugin

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The basket plugin finds frequent patterns of attributes in the data and returns the patterns that pass a frequency threshold in that data. A pattern represents a subset of the rows that have the same value across one or more columns. The basket plugin is based on the Apriori algorithm originally developed for basket analysis data mining.

Syntax

T | evaluate basket ([ Threshold, WeightColumn, MaxDimensions, CustomWildcard, CustomWildcard, ... ])

Learn more about syntax conventions.

Parameters

Name Type Required Description
Threshold long A double in the range of 0.015 to 1 that sets the minimal ratio of the rows to be considered frequent. Patterns with a smaller ratio won't be returned. The default value is 0.05. To use the default value, input the tilde: ~.

Example: T | evaluate basket(0.02)
WeightColumn string The column name to use to consider each row in the input according to the specified weight. Must be a name of a numeric type column, such as int, long, real. By default, each row has a weight of 1. To use the default value, input the tilde: ~. A common use of a weight column is to take into account sampling or bucketing/aggregation of the data that is already embedded into each row.

Example: T | evaluate basket('~', sample_Count)
MaxDimensions int Sets the maximal number of uncorrelated dimensions per basket, limited by default, to minimize the query runtime. The default is 5. To use the default value, input the tilde: ~.

Example: T | evaluate basket('~', '~', 3)
CustomWildcard string Sets the wildcard value for a specific type in the result table that will indicate that the current pattern doesn't have a restriction on this column. The default is null except for string columns whose default value is an empty string. If the default is a good value in the data, a different wildcard value should be used, such as *. To use the default value, input the tilde: ~.

Example: T | evaluate basket('~', '~', '~', '*', int(-1), double(-1), long(0), datetime(1900-1-1))

Note

To specify an optional parameter that follows an optional parameter, make sure to provide a value for the preceding optional parameter. For more information, see Working with optional parameters.

Returns

The basket plugin returns frequent patterns that pass a ratio threshold. The default threshold is 0.05.

Each pattern is represented by a row in the results. The first column is the segment ID. The next two columns are the count and percentage of rows, from the original query that match the pattern. The remaining columns relate to the original query, with either a specific value from the column or a wildcard value, which is by default null, meaning a variable value.

Note

The algorithm uses sampling to determine the initial frequent values. Therefore, the results could slightly differ between multiple runs for patterns whose frequency is close to the threshold.

Example

Run the query

StormEvents
| where monthofyear(StartTime) == 5
| extend Damage = iff(DamageCrops + DamageProperty > 0 , "YES" , "NO")
| project State, EventType, Damage, DamageCrops
| evaluate basket(0.2)

Output

SegmentId Count Percent State EventType Damage DamageCrops
0 4574 77.7 NO 0
1 2278 38.7 Hail NO 0
2 5675 96.4 0
3 2371 40.3 Hail 0
4 1279 21.7 Thunderstorm Wind 0
5 2468 41.9 Hail
6 1310 22.3 YES
7 1291 21.9 Thunderstorm Wind

Example with custom wildcards

Run the query

StormEvents
| where monthofyear(StartTime) == 5
| extend Damage = iff(DamageCrops + DamageProperty > 0 , "YES" , "NO")
| project State, EventType, Damage, DamageCrops
| evaluate basket(0.2, '~', '~', '*', int(-1))

Output

SegmentId Count Percent State EventType Damage DamageCrops
0 4574 77.7 * * NO 0
1 2278 38.7 * Hail NO 0
2 5675 96.4 * * * 0
3 2371 40.3 * Hail * 0
4 1279 21.7 * Thunderstorm Wind * 0
5 2468 41.9 * Hail * -1
6 1310 22.3 * * YES -1
7 1291 21.9 * Thunderstorm Wind * -1