This library provides an abstract class and CLOS APIs for the trainable funcallable instances.
The library is almost blank; It has no actual implementations in it. Its sole purpose is to provide the interface for a machine learning model.
Class TRAINABLE-OBJECT (SERIALIZABLE-OBJECT) Generic Function (train model input output &key verbose val-input val-output test-input test-output &allow-other-keys) Generic Function (evaluate model input output &key verbose &allow-other-keys) Generic Function (predict model input &key verbose &allow-other-keys)
This library is at least tested on implementation listed below:
- SBCL 1.4.12 on X86-64 Linux 4.4.0-142-generic (author’s environment)
Also, it depends on the following libraries:
- trivia by Masataro Asai : NON-optimized pattern matcher compatible with OPTIMA, with extensible optimizer interface and clean codebase
- alexandria by Nikodemus Siivola <email@example.com>, and others. : Alexandria is a collection of portable public domain utilities.
- iterate by ** : Jonathan Amsterdam’s iterator/gatherer/accumulator facility
- closer-mop by Pascal Costanza : Closer to MOP is a compatibility layer that rectifies many of the absent or incorrect CLOS MOP features across a broad range of Common Lisp implementations.
Author, License, Copyright
Licensed under LGPL v3.
Copyright (c) 2019 Masataro Asai (firstname.lastname@example.org) Copyright (c) 2019 IBM Corporation