Performance file

General Format

The first line of the result file is a column header. The possible labels are defined in the file fis.h:

• "OBS": The observed output, part of the data set
• "INF": The inferred output
• "Al": Alarm risen while inferring (see below)
• "ClINF": Inferred class label, for crisp output and classification flag
• "CLAl": Alarm risen while inferring (see below)
• "Err": Difference between inferred and observed output
• "Bl": Blank flag, 1 if this item is considered as blank, o otherwise
• "CErr2": square cumulated error over the previous examples.

WARNING: The cumulated error does not take into account the blank examples.

The first column holds the observed output, if it is available in the data file, as inference can also be done without an observed output.
The second one gives, when the observed output value is available, the difference between observed and inferred values.
A variable number of columns follows, depending on the output nature.

Output	Classif	Defuzzification	Field #	Available fields
crisp	yes	sugeno	4	infered v.	Alarm	infered class	Alarm
crisp	no	sugeno	2	inferred v.	Alarm
crisp		MaxCrisp	2	inferred v.	Alarm
fuzzy	yes	sugeno/area	n+2	infered v.	Alarm	$\mu_1,\mu_2\ldots\mu_n$
fuzzy	no	sugeno/area	2	infered v.	Alarm
fuzzy	yes	MeanMax	n+2	infered v.	Alarm	$\mu_1,\mu_2\ldots\mu_n$
fuzzy	no	MeanMax	2	infered v.	Alarm

Note: $\mu_1,\mu_2\ldots\mu_n$ are available if the example activates at least one rule. For a fuzzy output defuzzified with sugeno ou area operators, they are equal to the inferred output value membership degrees to MF $1,2\ldots n$. For a fuzzy output defuzzified with a MeanMax operator, or for a crisp output obtained through a MaxCrisp operator, they represent the matching degree of all possible outputs: MF values for a fuzzy output, or real values for a crisp output.

The column Bl is 1 if the item is inactive, 0 otherwise. Finally, the last column gives the current value of the performance index.

Available alarm values:

Integer values which depend on the defuzzification operator:

• NOTHING (Value 0): All types. Everything is normal.

• NO_ACTIVE_RULE (Value 1): All types. The example does not fire any rule of the rule base.

• AMBIGUITY (Value 2): SugenoClassif (Crisp output) and MaxCrisp. The difference between the two main classes is less than a threshold (default value AMBIGU_THRES = 0.1).

• NON_CONNEX_AREA (Value 3): WeArea - Set when the area defined by the fired fuzzy sets (threshold set to MIN_THRES = 0.1 by default) is non connex.

• NON_CONNEX_SEGMENT (Value 4): MeanMax - Set when the max corresponds to two fuzzy sets (with a tolerance threshold set by default to EQUALITY_THRES = 0.1) and the resulting segment is non connex.

The performance function also computes the coverage index, which depends on the minimum matching degree given as an argument.