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Provides an metaclass and APIs for the trainable funcallable instances. (WIP)
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README.org

Trainable-Object

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.

API

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)

Dependencies

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 <nikodemus@sb-studio.net>, 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.

Installation

Author, License, Copyright

Licensed under LGPL v3.

Copyright (c) 2019 Masataro Asai (guicho2.71828@gmail.com) Copyright (c) 2019 IBM Corporation

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