API Reference#

This section provides detailed documentation for all Ex-Fuzzy classes, functions, and modules.

Core Modules#

`fuzzy_sets`	Fuzzy Sets Module for Ex-Fuzzy Library
`evolutionary_fit`	Evolutionary Optimization for Fuzzy Rule Base Learning
`rules`	Fuzzy Rules and Inference Engine for Ex-Fuzzy Library
`classifiers`	Fuzzy Classification Algorithms for Ex-Fuzzy Library
`eval_tools`	Evaluation Tools for Fuzzy Rule-Based Models

Analysis and Visualization#

`pattern_stability`	Pattern Stability Analysis Module for Ex-Fuzzy Library
`vis_rules`	Rule Visualization Module for Ex-Fuzzy Library
`cognitive_maps`	Fuzzy Cognitive Maps for Ex-Fuzzy Library
`temporal`	Temporal Fuzzy Sets Module for Ex-Fuzzy Library

Utilities and Support#

`utils`	Utility Functions for Ex-Fuzzy Library
`persistence`	Persistence Module for Ex-Fuzzy Library
`bootstrapping_test`	Bootstrap Statistical Testing Module for Ex-Fuzzy Library
`eval_rules`	This file contains the classes to perform rule classification evaluation.

Quick Reference#

Most Common Classes#

`evolutionary_fit.BaseFuzzyRulesClassifier`([...])	Class that is used as a classifier for a fuzzy rule based system.
`fuzzy_sets.fuzzyVariable`(name, fuzzy_sets[, ...])	Fuzzy Variable Container and Management Class.
`fuzzy_sets.FS`(name, membership_parameters, ...)	Base class for Type-1 fuzzy sets (Zadeh fuzzy sets).
`rules.RuleSimple`(antecedents[, consequent, ...])	Simplified Rule Representation for Optimized Computation.
`rules.RuleBase`(antecedents, rules[, ...])	Class optimized to work with multiple rules at the same time.
`eval_tools.FuzzyEvaluator`(fl_classifier)	Comprehensive evaluation and analysis tool for fuzzy rule-based classifiers.

Most Common Functions#

`vis_rules.plot_fuzzy_variable`(fuzzy_variable)	Plots a fuzzy variable using trapezoidal membership functions.
`pattern_stability.pattern_stabilizer`(X, y[, ...])

By Category#

Fuzzy Set Operations#

`fuzzy_sets.FS`(name, membership_parameters, ...)	Base class for Type-1 fuzzy sets (Zadeh fuzzy sets).
`fuzzy_sets.gaussianFS`(name, ...)	Gaussian Type-1 Fuzzy Set Implementation.
`fuzzy_sets.gaussianIVFS`(name, ...[, ...])	Gaussian Interval-Valued (Type-2) Fuzzy Set Implementation.
`fuzzy_sets.categoricalFS`(name, category)
`fuzzy_sets.fuzzyVariable`(name, fuzzy_sets[, ...])	Fuzzy Variable Container and Management Class.

Classification#

`evolutionary_fit.BaseFuzzyRulesClassifier`([...])	Class that is used as a classifier for a fuzzy rule based system.
`classifiers.RuleMineClassifier`([nRules, ...])	A classifier that works by mining a set of candidate rules with a minimum support, confidence and lift, and then using a genetic algorithm that chooses the optimal combination of those rules.

Rule Management#

`rules.RuleSimple`(antecedents[, consequent, ...])	Simplified Rule Representation for Optimized Computation.
`rules.RuleBase`(antecedents, rules[, ...])	Class optimized to work with multiple rules at the same time.
`rules.MasterRuleBase`(rule_base[, ...])	This Class encompasses a list of rule bases where each one corresponds to a different class.
`rules.generate_rule_string`(rule, antecedents)	Generates a string with the rule.

Evaluation and Metrics#

eval_tools.FuzzyEvaluator(fl_classifier)

Comprehensive evaluation and analysis tool for fuzzy rule-based classifiers.

Visualization#

`vis_rules.plot_fuzzy_variable`(fuzzy_variable)	Plots a fuzzy variable using trapezoidal membership functions.
`pattern_stability.pattern_stabilizer.pie_chart_basic`(...)	Generates a pie chart for the variable usage in the rule bases.

Model Persistence#

`persistence.save_fuzzy_variables`(fuzzy_variables)	Save multiple fuzzy variables to a text string representation.
`persistence.load_fuzzy_variables`(...)	Load fuzzy variables from a text string representation.

Constants and Enums#

fuzzy_sets.FUZZY_SETS(value[, names, ...])

Type Hints#

Ex-Fuzzy uses type hints throughout the codebase. Here are the most common types:

from typing import List, Dict, Tuple, Optional, Union
import numpy as np
import pandas as pd

# Common type aliases used in Ex-Fuzzy
ArrayLike = Union[np.ndarray, List, Tuple]
DataFrame = pd.DataFrame
FuzzySet = 'ex_fuzzy.fuzzy_sets.FS'
FuzzyVariable = 'ex_fuzzy.fuzzy_sets.fuzzyVariable'
Rule = 'ex_fuzzy.rules.RuleSimple'