Version: 0.5.x

AISP - API

Welcome to the AISP (Artificial Immune System Package) api. This documentation demonstrates the package public API.

Core Modules (`aisp.base`)

Fundamental abstractions and base classes that define core interfaces of package.

Class	Description
`BaseClassifier`	Abstract base class for classification algorithms.
`BaseClusterer`	Abstract base class for clustering algorithms.
`BaseOptimizer`	Abstract base class for optimization algorithms.

Core structures and support utilities for implementations immune.

Module	Description
`cell`	Representation of immune system cells.
`mutation`	Functions to generate mutated clones and simulate clonal expansion.
`populations`	Provide utility functions for generating antibody populations in immunological algorithms.

supervised learning algorithms based on negative selection, the immune systems process of distinguishing self from not-self.

Class	Description
`RNSA`	A supervised learning algorithm for classification that uses real-valued detectors.
`BNSA`	A supervised learning algorithm for classification that uses binary detectors.

Algorithms inspired by the process of antibody proliferation to detecting an antigen.

Class	Description
`AIRS`	A supervised learning algorithm for classification tasks based on the clonal selection principle.
`Clonalg`	Implementation of the clonal selection algorithm for optimization, adapted for both minimization and maximization of cost functions in binary, continuous, and permutation problems.

Algorithms based on Network Theory Algorithms proposed by Jerne.

Class	Description
`AiNet`	An unsupervised learning algorithm for clustering, based on the theory of immune networks.

Utility functions and helpers for development.

Module	Description
`display`	Utility functions for displaying algorithm information.
`distance`	Utility functions for distance between arrays with numba decorators.
`metrics`	Utility functions for measuring accuracy and performance.
`multiclass`	Utility functions for handling classes with multiple categories.
`sanitizers`	Utility functions for validation and treatment of parameters.
`types`	Defines type aliases used throughout the project to improve readability.
`validation`	Contains functions responsible for validating data types.

Custom warnings and errors.