Process Mining Objects in Expression Language - Revision history

Ollvihe: /* EventLog */

2023-05-01T20:09:59Z

EventLog

← Older revision		Revision as of 20:09, 1 May 2023
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	\|}		\|}

	Eventlog related functions:		Eventlog related generic functions:
	{\| class="wikitable"		{\| class="wikitable"
	!'''Function'''		!'''Function'''
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	\|}		\|}

	Eventlog related properties:		Eventlog related generic properties:
	{\| class="wikitable"		{\| class="wikitable"
	!'''Function'''		!'''Function'''

Ollvihe: /* EventLog */

2023-05-01T20:09:24Z

EventLog

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 |}
 {| class="wikitable"
 !'''Function'''
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 ||
 Returns EventLog object corresponding to the provided filter Id.
 |}

Ollvihe: /* EventLog */

2022-12-01T19:23:45Z

EventLog

@@ Line 473: / Line 473: @@
 </pre>
 |-
-||FindRootCauses (DataFrame)
+||[[FindRootCauses_Function|FindRootCauses]] (DataFrame)
 ||
 Settings (Dictionary)
 ||
 |}

Ollvihe at 12:03, 24 November 2022

2022-11-24T12:03:56Z

← Older revision		Revision as of 12:03, 24 November 2022
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	Examples:		Examples:
	<pre>		<pre>
	~~Let("~~myConformanceModel", DesignModelFromXml(xml));		let myConformanceModel = DesignModelFromXml(xml);
	~~Let("~~myEventLog", EventLogById(1));		let myEventLog = EventLogById(1);
	~~Let("~~cases", OrderBy(EventLogById(1).Cases, Name));		let cases = OrderBy(EventLogById(1).Cases, Name);
	cases.(		cases.(
	Let("analysis",AnalyzeConformance(myConformanceModel)),		Let("analysis",AnalyzeConformance(myConformanceModel)),
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	Examples:		Examples:
	<pre>		<pre>
	~~Let("~~myConformanceModel", DesignModelFromXml(xml));		let myConformanceModel = DesignModelFromXml(xml);
	~~Let("~~myEventlog", EventLogById(1));		let myEventlog = EventLogById(1);
	Count(myEventlog.Cases.Where(IsConformant(myConformanceModel))) / Count(myEventlog.Cases)		Count(myEventlog.Cases.Where(IsConformant(myConformanceModel))) / Count(myEventlog.Cases)

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	Example:		Example:
	<pre>		<pre>
	~~Let("~~cm", DesignModelFromXml(xml));		let cm = DesignModelFromXml(xml);
	~~Let("~~el", EventLogById(1));		let el = EventLogById(1);
	~~Let("~~vars", OrderByDescending(EventLogById(1).Variations, CaseCount));		let vars = OrderByDescending(EventLogById(1).Variations, CaseCount);
	vars.(		vars.(
	Let("analysis",AnalyzeConformance(cm)),		Let("analysis",AnalyzeConformance(cm)),

Ollvihe: /* EventLog */

2022-11-03T20:32:16Z

EventLog

← Older revision		Revision as of 20:32, 3 November 2022
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	* '''Selection''': [[Filtering_in_QPR_ProcessAnalyzer_Queries\|Filter]] to define the investigated feature or phenomenon to find root causes for.		* '''Selection''': [[Filtering_in_QPR_ProcessAnalyzer_Queries\|Filter]] to define the investigated feature or phenomenon to find root causes for.
	* '''CaseAttributeTypes''': Searches root causes only for the defined case attributes. If null, search for all case attributes. Applicable only when ''Types'' contains ''CaseAttributeValue''.		* '''CaseAttributeTypes''': Searches root causes only for the defined case attributes. If null, search for all case attributes. Applicable only when ''Types'' contains ''CaseAttributeValue''.
	* '''MaximumRowCount''': Maximum number of rows (i.e. root causes) to return. ~~Rroot~~ causes are always returned starting from the most important one.		* '''MaximumRowCount''': Maximum number of rows (i.e. root causes) to return. Root causes are always returned starting from the most important one.
	* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.		* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.
	*'''WeightingExpression''': Expression to define weights for each case, used additionally for the root causes calculation. When not defined, all cases have equal weight. If a weight for a case is ''null'', the case is filtered out from the calculation. Weighting can be used when some cases are more important than others, for example the Cost attribute can be used as weights to emphasize cases that have higher costs or value. The basic principle of the weighting is that instead of case counts, the calculation is based on the weights. The non-weighting mode can be considered as weighting where each case has the weight of one.		*'''WeightingExpression''': Expression to define weights for each case, used additionally for the root causes calculation. When not defined, all cases have equal weight. If a weight for a case is ''null'', the case is filtered out from the calculation. Weighting can be used when some cases are more important than others, for example the Cost attribute can be used as weights to emphasize cases that have higher costs or value. The basic principle of the weighting is that instead of case counts, the calculation is based on the weights. The non-weighting mode can be considered as weighting where each case has the weight of one.

Ollvihe: /* EventLog */

2022-11-03T10:42:53Z

EventLog

← Older revision		Revision as of 10:42, 3 November 2022
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	* '''MaximumRowCount''': Maximum number of rows (i.e. root causes) to return. Rroot causes are always returned starting from the most important one.		* '''MaximumRowCount''': Maximum number of rows (i.e. root causes) to return. Rroot causes are always returned starting from the most important one.
	* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.		* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.
	*'''WeightingExpression''': Expression to define weights for each case used for the root causes calculation. When not defined, all cases have equal weight. If ~~weights~~ for a case is null, the case is filtered out from the calculation. Weighting can be used when some cases are more important than others, for example ~~weighting~~ can be ~~done~~ based on the ~~Cost attribute~~.		*'''WeightingExpression''': Expression to define weights for each case, used additionally for the root causes calculation. When not defined, all cases have equal weight. If a weight for a case is ''null'', the case is filtered out from the calculation. Weighting can be used when some cases are more important than others, for example the Cost attribute can be used as weights to emphasize cases that have higher costs or value. The basic principle of the weighting is that instead of case counts, the calculation is based on the weights. The non-weighting mode can be considered as weighting where each case has the weight of one.

	The result is a DataFrame where each row represents an individual root cause. Identified root causes are features that are common among a set of cases (i.e. all cases where Region is Dallas). Root causes are returned in the order or importance, and either positively or negatively correlated, or both (determined by the ''correlation'' setting).		The result is a DataFrame where each row represents an individual root cause. Identified root causes are features that are common among a set of cases (i.e. all cases where Region is Dallas). Root causes are returned in the order or importance, and either positively or negatively correlated, or both (determined by the ''correlation'' setting).
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	* '''Selected''': Number of cases in the selected cases (''Selection'' parameter) having the found root cause, i.e. common cases between Total and TotalSelected.		* '''Selected''': Number of cases in the selected cases (''Selection'' parameter) having the found root cause, i.e. common cases between Total and TotalSelected.
	* '''Compared''': Number of cases in the selected cases (''Selection'' parameter) that doesn't have the found root cause. Formula: Total - Selected.		* '''Compared''': Number of cases in the selected cases (''Selection'' parameter) that doesn't have the found root cause. Formula: Total - Selected.
	* '''Contribution''': Describes in how many cases this root cause contributes to the investigated phenomenon, i.e. how many cases more there are in the root causes cases comparison to the average among all cases in the eventlog. Formula: Selected - Total * TotalSelected / TotalEventLog. When weighting is in use, the ~~Contribution~~ is not the number of cases, but ~~corresponding weighted value~~.		* '''Contribution''': Describes in how many cases this root cause contributes to the investigated phenomenon, i.e. how many cases more there are in the root causes cases comparison to the average among all cases in the eventlog. Formula: Selected - Total * TotalSelected / TotalEventLog. When weighting is in use, the calculation is not based on the number of cases, but the weights instead.
	* '''ContributionPercentage''': Describes how large portion of the existence of the investigated phenomenon this root causes explains. Formula: Contribution / TotalSelected = (Selected - Total * TotalSelected / TotalEventLog) / TotalSelected = Selected / TotalSelected - Total / TotalEventLog.		* '''ContributionPercentage''': Describes how large portion of the existence of the investigated phenomenon this root causes explains. Formula: Contribution / TotalSelected = (Selected - Total * TotalSelected / TotalEventLog) / TotalSelected = Selected / TotalSelected - Total / TotalEventLog. When weighting is in use, the calculation is not based on the number of cases, but the weights instead.
	* '''SelectedPercentage''': Percentage of cases that belong to the selected cases in the cases having the found root cause. Formula: Selected / Total.		* '''SelectedPercentage''': Percentage of cases that belong to the selected cases in the cases having the found root cause. Formula: Selected / Total. When weighting is in use, the calculation is not based on the number of cases, but the weights instead.
	* '''DifferencePercentage''': Difference between the percentage in the root cause cases and the all cases in the eventlog. Formula: Selected / Total - TotalSelected / TotalEventLog.		* '''DifferencePercentage''': Difference between the percentage in the root cause cases and the all cases in the eventlog. Formula: Selected / Total - TotalSelected / TotalEventLog. When weighting is in use, the calculation is not based on the number of cases, but the weights instead.
	* '''SelectedWeight''': This column is only when weighting is in use, ~~and it~~'~~s the~~ ''~~Selected~~'' ~~where~~ the weights ~~are included~~.
	* '''ComparedWeight''': ~~This column is only when weighting is in use, and it's~~ the ~~''Compared'' where~~ the ~~weights are included~~.		When the weighting is in use (i.e., WeightingExpression is defined), there are the following additional columns:
	* '''TotalWeight''': ~~This column is only when weighting is in use, and it's the ''Total'' where~~ the weights ~~are included~~.		* '''SelectedWeight''': Sum of the weights of the selected cases.
			* '''ComparedWeight''': Sum of the weights of the compared cases.
			* '''TotalWeight''': Sum of the weights of all cases.

	In the above formulas, ''TotalSelected'' are the number of cases in the eventlog that belong to the selected cases (i.e. the '''Selection'' parameter). ''TotalEventLog'' are the number of cases in the eventlog where the root causes are searched from.		In the above formulas, ''TotalSelected'' are the number of cases in the eventlog that belong to the selected cases (i.e. the '''Selection'' parameter). ''TotalEventLog'' are the number of cases in the eventlog where the root causes are searched from.
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	},		},
	"CaseAttributeTypes": ["Account Manager", "Case start month"],		"CaseAttributeTypes": ["Account Manager", "Case start month"],
	"MaximumRowCount": 20		"MaximumRowCount": 20,
			"WeightingExpression": "Attribute(\"Cost\")"
	});		});
	</pre>		</pre>

Ollvihe: /* EventLog */

2022-11-03T10:22:41Z

EventLog

← Older revision		Revision as of 10:22, 3 November 2022
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	* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.		* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.
	*'''WeightingExpression''': Expression to define weights for each case used for the root causes calculation. When not defined, all cases have equal weight. If weights for a case is null, the case is filtered out from the calculation. Weighting can be used when some cases are more important than others, for example weighting can be done based on the Cost attribute.		*'''WeightingExpression''': Expression to define weights for each case used for the root causes calculation. When not defined, all cases have equal weight. If weights for a case is null, the case is filtered out from the calculation. Weighting can be used when some cases are more important than others, for example weighting can be done based on the Cost attribute.
	* (future) '''Correlation''': In the identified root causes, the direction of correlation to the investigated phenomenon can be either positive or negative. This setting determines whether to return only cases with positive correlation (''positive''), negative correlation (''negative''), or both cases (''both'').

	The result is a DataFrame where each row represents an individual root cause. Identified root causes are features that are common among a set of cases (i.e. all cases where Region is Dallas). Root causes are returned in the order or importance, and either positively or negatively correlated, or both (determined by the ''correlation'' setting).		The result is a DataFrame where each row represents an individual root cause. Identified root causes are features that are common among a set of cases (i.e. all cases where Region is Dallas). Root causes are returned in the order or importance, and either positively or negatively correlated, or both (determined by the ''correlation'' setting).
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	* '''SelectedPercentage''': Percentage of cases that belong to the selected cases in the cases having the found root cause. Formula: Selected / Total.		* '''SelectedPercentage''': Percentage of cases that belong to the selected cases in the cases having the found root cause. Formula: Selected / Total.
	* '''DifferencePercentage''': Difference between the percentage in the root cause cases and the all cases in the eventlog. Formula: Selected / Total - TotalSelected / TotalEventLog.		* '''DifferencePercentage''': Difference between the percentage in the root cause cases and the all cases in the eventlog. Formula: Selected / Total - TotalSelected / TotalEventLog.
			* '''SelectedWeight''': This column is only when weighting is in use, and it's the ''Selected'' where the weights are included.
			* '''ComparedWeight''': This column is only when weighting is in use, and it's the ''Compared'' where the weights are included.
			* '''TotalWeight''': This column is only when weighting is in use, and it's the ''Total'' where the weights are included.

	In the above formulas, ''TotalSelected'' are the number of cases in the eventlog that belong to the selected cases (i.e. the '''Selection'' parameter). ''TotalEventLog'' are the number of cases in the eventlog where the root causes are searched from.		In the above formulas, ''TotalSelected'' are the number of cases in the eventlog that belong to the selected cases (i.e. the '''Selection'' parameter). ''TotalEventLog'' are the number of cases in the eventlog where the root causes are searched from.

Ollvihe: /* EventLog */

2022-10-31T20:58:13Z

EventLog

← Older revision		Revision as of 20:58, 31 October 2022
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	Settings (Dictionary)		Settings (Dictionary)
	\|\|		\|\|
	Performs the [[Root_Causes\|root causes analysis]] for eventlog based on the given settings, and returns results as a DataFrame. Root causes are features that correlate with the ~~investigate~~ phenomenon in the selected set of cases.		Performs the [[Root_Causes\|root causes analysis]] for eventlog based on the given settings, and returns results as a DataFrame. Root causes are features that correlate with the investigated phenomenon in the selected set of cases.

	Following parameters can be used:		Following parameters can be used:
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	* '''Selected''': Number of cases in the selected cases (''Selection'' parameter) having the found root cause, i.e. common cases between Total and TotalSelected.		* '''Selected''': Number of cases in the selected cases (''Selection'' parameter) having the found root cause, i.e. common cases between Total and TotalSelected.
	* '''Compared''': Number of cases in the selected cases (''Selection'' parameter) that doesn't have the found root cause. Formula: Total - Selected.		* '''Compared''': Number of cases in the selected cases (''Selection'' parameter) that doesn't have the found root cause. Formula: Total - Selected.
	* '''Contribution''': Describes in how many cases this root cause contributes to the ~~investigate~~ phenomenon, i.e. how many cases more there are in the root causes cases comparison to the average among all cases in the eventlog. Formula: Selected - Total * TotalSelected / TotalEventLog. When weighting is in use, the Contribution is not the number of cases, but corresponding weighted value.		* '''Contribution''': Describes in how many cases this root cause contributes to the investigated phenomenon, i.e. how many cases more there are in the root causes cases comparison to the average among all cases in the eventlog. Formula: Selected - Total * TotalSelected / TotalEventLog. When weighting is in use, the Contribution is not the number of cases, but corresponding weighted value.
	* '''ContributionPercentage''': Describes how large portion of the existence of the ~~investigate~~ phenomenon this root causes explains. Formula: Contribution / TotalSelected = (Selected - Total * TotalSelected / TotalEventLog) / TotalSelected = Selected / TotalSelected - Total / TotalEventLog.		* '''ContributionPercentage''': Describes how large portion of the existence of the investigated phenomenon this root causes explains. Formula: Contribution / TotalSelected = (Selected - Total * TotalSelected / TotalEventLog) / TotalSelected = Selected / TotalSelected - Total / TotalEventLog.
	* '''SelectedPercentage''': Percentage of cases that belong to the selected cases in the cases having the found root cause. Formula: Selected / Total.		* '''SelectedPercentage''': Percentage of cases that belong to the selected cases in the cases having the found root cause. Formula: Selected / Total.
	* '''DifferencePercentage''': Difference between the percentage in the root cause cases and the all cases in the eventlog. Formula: Selected / Total - TotalSelected / TotalEventLog.		* '''DifferencePercentage''': Difference between the percentage in the root cause cases and the all cases in the eventlog. Formula: Selected / Total - TotalSelected / TotalEventLog.

Ollvihe: /* EventLog */

2022-10-26T18:09:01Z

EventLog

← Older revision		Revision as of 18:09, 26 October 2022
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	* '''MaximumRowCount''': Maximum number of rows (i.e. root causes) to return. Rroot causes are always returned starting from the most important one.		* '''MaximumRowCount''': Maximum number of rows (i.e. root causes) to return. Rroot causes are always returned starting from the most important one.
	* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.		* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.
			*'''WeightingExpression''': Expression to define weights for each case used for the root causes calculation. When not defined, all cases have equal weight. If weights for a case is null, the case is filtered out from the calculation. Weighting can be used when some cases are more important than others, for example weighting can be done based on the Cost attribute.
	* (future) '''Correlation''': In the identified root causes, the direction of correlation to the investigated phenomenon can be either positive or negative. This setting determines whether to return only cases with positive correlation (''positive''), negative correlation (''negative''), or both cases (''both'').		* (future) '''Correlation''': In the identified root causes, the direction of correlation to the investigated phenomenon can be either positive or negative. This setting determines whether to return only cases with positive correlation (''positive''), negative correlation (''negative''), or both cases (''both'').

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	* '''Selected''': Number of cases in the selected cases (''Selection'' parameter) having the found root cause, i.e. common cases between Total and TotalSelected.		* '''Selected''': Number of cases in the selected cases (''Selection'' parameter) having the found root cause, i.e. common cases between Total and TotalSelected.
	* '''Compared''': Number of cases in the selected cases (''Selection'' parameter) that doesn't have the found root cause. Formula: Total - Selected.		* '''Compared''': Number of cases in the selected cases (''Selection'' parameter) that doesn't have the found root cause. Formula: Total - Selected.
	* '''Contribution''': Describes in how many cases this root cause contributes to the investigate phenomenon, i.e. how many cases more there are in the root causes cases comparison to the average among all cases in the eventlog. Formula: Selected - Total * TotalSelected / TotalEventLog.		* '''Contribution''': Describes in how many cases this root cause contributes to the investigate phenomenon, i.e. how many cases more there are in the root causes cases comparison to the average among all cases in the eventlog. Formula: Selected - Total * TotalSelected / TotalEventLog. When weighting is in use, the Contribution is not the number of cases, but corresponding weighted value.
	* '''ContributionPercentage''': Describes how large portion of the existence of the investigate phenomenon this root causes explains. Formula: Contribution / TotalSelected = (Selected - Total * TotalSelected / TotalEventLog) / TotalSelected = Selected / TotalSelected - Total / TotalEventLog.		* '''ContributionPercentage''': Describes how large portion of the existence of the investigate phenomenon this root causes explains. Formula: Contribution / TotalSelected = (Selected - Total * TotalSelected / TotalEventLog) / TotalSelected = Selected / TotalSelected - Total / TotalEventLog.
	* '''SelectedPercentage''': Percentage of cases that belong to the selected cases in the cases having the found root cause. Formula: Selected / Total.		* '''SelectedPercentage''': Percentage of cases that belong to the selected cases in the cases having the found root cause. Formula: Selected / Total.

Ollvihe: /* EventLog */

2022-08-31T09:30:52Z

EventLog

← Older revision		Revision as of 09:30, 31 August 2022
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	Settings (Dictionary)		Settings (Dictionary)
	\|\|		\|\|
	Performs the [[Root_Causes\|root causes analysis]] for ~~for the~~ eventlog based on the given settings, and returns results as a DataFrame. Root causes are features that correlate with the investigate phenomenon in the selected set of cases.		Performs the [[Root_Causes\|root causes analysis]] for eventlog based on the given settings, and returns results as a DataFrame. Root causes are features that correlate with the investigate phenomenon in the selected set of cases.

	Following ~~parameter~~ can be used:		Following parameters can be used:
	* '''Selection''': [[Filtering_in_QPR_ProcessAnalyzer_Queries\|Filter]] to define the investigated phenomenon to find root causes for.		* '''Selection''': [[Filtering_in_QPR_ProcessAnalyzer_Queries\|Filter]] to define the investigated feature or phenomenon to find root causes for.
	* '''CaseAttributeTypes''': ~~Search~~ root causes only for the defined case attributes ~~(if~~ null, search for all case attributes). Applicable only when ''Types'' is ''CaseAttributeValue''.		* '''CaseAttributeTypes''': Searches root causes only for the defined case attributes. If null, search for all case attributes. Applicable only when ''Types'' contains ''CaseAttributeValue''.
	* '''MaximumRowCount''': Maximum number of rows (i.e. root causes) to return ~~(root~~ causes are always returned starting from the most important one).		* '''MaximumRowCount''': Maximum number of rows (i.e. root causes) to return. Rroot causes are always returned starting from the most important one.
	* '''Types''': Types of root causes to search from the eventlog. ~~Supports~~ only CaseAttributeValue.		* '''Types''': Types of root causes to search from the eventlog. Currently, supports only CaseAttributeValue.
	* (future) '''Correlation''': In the identified root causes, the direction of correlation to the investigated phenomenon can be either positive or negative. This setting determines whether to return only cases with positive correlation (''positive''), negative correlation (''negative''), or both cases (''both'').		* (future) '''Correlation''': In the identified root causes, the direction of correlation to the investigated phenomenon can be either positive or negative. This setting determines whether to return only cases with positive correlation (''positive''), negative correlation (''negative''), or both cases (''both'').

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	},		},
	"CaseAttributeTypes": ["Account Manager", "Case start month"],		"CaseAttributeTypes": ["Account Manager", "Case start month"],
	~~"Correlation": "positive",~~
	"MaximumRowCount": 20		"MaximumRowCount": 20
	});		});