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https://github.com/guicho271828/trainable-object
Provides an metaclass and APIs for the trainable funcallable instances. (WIP)
https://github.com/guicho271828/trainable-object
Last synced: 29 days ago
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Provides an metaclass and APIs for the trainable funcallable instances. (WIP)
- Host: GitHub
- URL: https://github.com/guicho271828/trainable-object
- Owner: guicho271828
- License: other
- Created: 2019-12-23T04:46:04.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2019-12-23T04:46:32.000Z (about 5 years ago)
- Last Synced: 2024-10-15T14:10:58.270Z (3 months ago)
- Language: Common Lisp
- Size: 21.5 KB
- Stars: 5
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.org
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
* 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 , 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 ([email protected])
Copyright (c) 2019 IBM Corporation