In this package, you will find some utilities to apply fuzzy logic t-norms and t-conorms to datasets.
You can find all the information about the T-norms and T-conorms in the following links: - T-norms and T-conorms - Construction of T-norms
The inputs for the script are:
dataset-id
: (dataset-id) Dataset where norms are appliedfield-id1
: (string) Field ID or name of the first operandfield-id2
: (string) Field ID or name of the second operandnorms
: (list) List of norms to apply, with params if needed. See more information below.
The outputs for the script are:
fuzzy-dataset
: (dataset-id) Dataset with some new columns with the result of applying the norms (t-norms or t-conorms).
Fields used as operands must contain real values between 0 and 1. As they are logical values it doesn't make sense having values outside this range. In this case, the script will raise an error.
The script will create a new column in the dataset for each one of the
norms specified in the norms
list.
Bellow, you can find an example of the content of the norms
input:
["min-tnorm","product","lukasiewicz", "drastic-tnorm",
"nilpotent-min",["schweizer-sklar", 0.5], ["hamacher", 0,5]]
As you can see there are some norms that need a parameter, that has to be specified in this way.
These are the possibles t-norms:
- min-tnorm: Minimum t-norm. Also called the Gödel t-norm. No parameters.
- product: Product t-norm. The ordinary product of real numbers. No parameters.
- lukasiewicz: Łukasiewicz t-norm. No parameters.
- drastic-tnorm: Drastic t-norm. No parameters.
- nilpotent-min: Nilpotent minimum t-norm. No parameters.
- [schweizer-sklar p]: Schweizer–Sklar t-norms. Parameter p in the range [-∞, ∞]
- [hamacher p]: Hamacher t-norms. Parameter p in the range [0, ∞]
- [yager p]: Yager t-norms. Parameter p in the range [0, ∞]
- [aczel-alsina p]: Aczél–Alsina t-norms. Parameter p in the range [0, ∞]
- [dombi p]: Dombi t-norms. Parameter p in the range [0, ∞]
- [sugeno-weber p]: Sugeno–Weber t-norms. Parameter p in the range [-1, ∞]
These are the possible t-conorms:
- max-tconorm: Maximum t-norm. Dual to the minimum t-norm, is the smallest t-conorm. No parameters
- probabilistic: Probabilistic t-norm. It's dual to the product t-norm. No parameters.
- bounded: Bounded t-norm. It'ss dual to the Łukasiewicz t-norm. No parameters.
- drastic-tconorm: Drastic t-conorm. It's dual to the drastic t-norm. No paramters.
- nilpotent-max: Nilpotent maximum t-conorm. It's dual to the nilpotent minumum.
- einstein-sum: Einstein t-conorm. It's a dual to one of the Hamacher t-norms.
Tests are included for this whizzml script. You can find more info about the tests in the top-level readme file.