Skip to main content

XCSF learning classifier system: rule-based evolutionary machine learning

Project description

XCSF learning classifier system

License Linux Build MacOS Build Windows Build Latest Version DOI Codacy CodeFactor SonarCloud codecov Lines of Code PyPI package Python versions Downloads

An implementation of the XCSF learning classifier system that can be built as a stand-alone binary or as a Python library. XCSF is an accuracy-based online evolutionary machine learning system with locally approximating functions that compute classifier payoff prediction directly from the input state. It can be seen as a generalisation of XCS where the prediction is a scalar value. XCSF attempts to find solutions that are accurate and maximally general over the global input space, similar to most machine learning techniques. However, it maintains the additional power to adaptively subdivide the input space into simpler local approximations.

See the project wiki for details on features, how to build, run, and use as a Python library.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

xcsf-1.4.7.tar.gz (5.7 MB view details)

Uploaded Source

Built Distributions

xcsf-1.4.7-pp310-pypy310_pp73-win_amd64.whl (626.0 kB view details)

Uploaded PyPy Windows x86-64

xcsf-1.4.7-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (414.5 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

xcsf-1.4.7-pp310-pypy310_pp73-macosx_12_0_x86_64.whl (1.5 MB view details)

Uploaded PyPy macOS 12.0+ x86-64

xcsf-1.4.7-pp39-pypy39_pp73-win_amd64.whl (626.0 kB view details)

Uploaded PyPy Windows x86-64

xcsf-1.4.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (414.3 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

xcsf-1.4.7-pp39-pypy39_pp73-macosx_12_0_x86_64.whl (1.5 MB view details)

Uploaded PyPy macOS 12.0+ x86-64

xcsf-1.4.7-cp313-cp313-win_amd64.whl (630.8 kB view details)

Uploaded CPython 3.13 Windows x86-64

xcsf-1.4.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (420.6 kB view details)

Uploaded CPython 3.13 manylinux: glibc 2.17+ x86-64

xcsf-1.4.7-cp313-cp313-macosx_14_0_arm64.whl (1.4 MB view details)

Uploaded CPython 3.13 macOS 14.0+ ARM64

xcsf-1.4.7-cp313-cp313-macosx_12_0_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.13 macOS 12.0+ x86-64

xcsf-1.4.7-cp312-cp312-win_amd64.whl (630.5 kB view details)

Uploaded CPython 3.12 Windows x86-64

xcsf-1.4.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (420.3 kB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

xcsf-1.4.7-cp312-cp312-macosx_14_0_arm64.whl (1.4 MB view details)

Uploaded CPython 3.12 macOS 14.0+ ARM64

xcsf-1.4.7-cp312-cp312-macosx_12_0_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.12 macOS 12.0+ x86-64

xcsf-1.4.7-cp311-cp311-win_amd64.whl (631.1 kB view details)

Uploaded CPython 3.11 Windows x86-64

xcsf-1.4.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (421.0 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

xcsf-1.4.7-cp311-cp311-macosx_14_0_arm64.whl (1.4 MB view details)

Uploaded CPython 3.11 macOS 14.0+ ARM64

xcsf-1.4.7-cp311-cp311-macosx_12_0_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.11 macOS 12.0+ x86-64

xcsf-1.4.7-cp310-cp310-win_amd64.whl (630.0 kB view details)

Uploaded CPython 3.10 Windows x86-64

xcsf-1.4.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (419.3 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

xcsf-1.4.7-cp310-cp310-macosx_14_0_arm64.whl (1.4 MB view details)

Uploaded CPython 3.10 macOS 14.0+ ARM64

xcsf-1.4.7-cp310-cp310-macosx_12_0_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.10 macOS 12.0+ x86-64

xcsf-1.4.7-cp39-cp39-win_amd64.whl (630.3 kB view details)

Uploaded CPython 3.9 Windows x86-64

xcsf-1.4.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (419.6 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

xcsf-1.4.7-cp39-cp39-macosx_14_0_arm64.whl (1.4 MB view details)

Uploaded CPython 3.9 macOS 14.0+ ARM64

xcsf-1.4.7-cp39-cp39-macosx_12_0_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.9 macOS 12.0+ x86-64

File details

Details for the file xcsf-1.4.7.tar.gz.

File metadata

  • Download URL: xcsf-1.4.7.tar.gz
  • Upload date:
  • Size: 5.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for xcsf-1.4.7.tar.gz
Algorithm Hash digest
SHA256 92b7b2efcdda072c5df7d8943c905763e67194f33271e69b871453fdd10351db
MD5 b42c67bbee59b90bacaf7c1c03800511
BLAKE2b-256 a12b7c563dad2fb6319febcd0c78b0792cfdcf02792f0201e63dae72575a331f

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-pp310-pypy310_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-pp310-pypy310_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 e99063a2b0f0c10c9dec91a5a5f59c90f7f0bbd542394b9333814b53f04d9fa1
MD5 ba1a0a30dea207d39f6a45b74c267aaf
BLAKE2b-256 33d55099c7ad78e5be8565d89e1e2152fca047368ab7f6dcdce1c2d01a80805d

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 15a601a740f04f380fe11d764696da2df0e89c668dd5e5b2b1524a24a99190d4
MD5 2e6d2be0a4225fe400649ce8d87f0e0a
BLAKE2b-256 1d7b1dbb5b2dd1579158c7903e5691c4c2471ff7201631698789a20d61f5a190

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-pp310-pypy310_pp73-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-pp310-pypy310_pp73-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 c4ef69ae141de158e11698eb1236b9c4662051ae5eec489142b789766f9361f0
MD5 7e0e67f86d3dc14dde20e9afd89e5f0d
BLAKE2b-256 02dda0e924b0c138424944d5bff08b7fece0f4f71f6bc052c0225378c1869348

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 94b362b09e3ce291f74c0ee624526213b96ef5a4f722d6c18b32e2ea78ba6fa8
MD5 a3dc185603041917e7a87dd60f670f72
BLAKE2b-256 bdbdc69cbd14ffeeed8c00c082973387b5b17273ffca57c595dc16d5d56d827c

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 eb985d52546dee7de6ecceb22ee2076d87d02317e1c1f1df1888d3fbae908731
MD5 5d189075d4b17ccdf221e71232d4cd7a
BLAKE2b-256 ae3fac8e96c306e80f683f214b6ffad166f6300dbf4d2bfb776e78b8810778df

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-pp39-pypy39_pp73-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-pp39-pypy39_pp73-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 fc4b35cb1a035dfb52ff19596772833a92d6cb6ebc95fffbd7a5654d09002f10
MD5 f23d4adc8af564542be2fed1cbdd1cb7
BLAKE2b-256 086d364d24af9d05b35dcfbcc5996701a7f74f33ffd460d15533826eee5f9963

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: xcsf-1.4.7-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 630.8 kB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for xcsf-1.4.7-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 82355b9082a0a79086ea6f9527cc35365f945d78eb6b4e4db67be6b7b83e8d44
MD5 46f3e0fccc957c5662bc7641bcfdd648
BLAKE2b-256 95a33be2da48bfc9861dde3873886f33807d81f3903d1b4b474d62c3264f4ae1

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c15baf27e17cc99a8ba30803dd22a3c15b5f5e67888dd711a963ba5cdf146bad
MD5 3bb6e81c294ab924db786da6f990b1a2
BLAKE2b-256 3cf4cc02080207de007eaf093cd584281c213dbd857922193188d5bbe3ee2d16

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp313-cp313-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp313-cp313-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 f1edd8a29f96f7c237a7866807be8fb1abcaea5a3429652ed61cf044d2bd1c7d
MD5 01753e27d1cff527aa190a28058bc330
BLAKE2b-256 c337bb07800e20200fcbb4a51740dac6425999bcea413f2754be7f57a07f4c4a

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp313-cp313-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp313-cp313-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 94b8c38daed414129eb27373cbcba4f55b9231091d5cc1297b20ac58d0df6547
MD5 92c8334815c3215f2d9c196da09b526c
BLAKE2b-256 190d75787bfc5fb687e4d27f17290fcb97f7b96664b735040b22e680a6b75523

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: xcsf-1.4.7-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 630.5 kB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for xcsf-1.4.7-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 95e9fdba3ec41132bea57e6f1e25809c74ac23549345429834c29a86d2d86f0b
MD5 91440c04fb3956a157605a0c5f8fa35a
BLAKE2b-256 4be861f407d5c8a47aa96f431cecbbc588b90a3bc6bf9cafb8bb31c131233ad9

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5f47c1c80acd9487d2d8d8f35f44b828ddeceade3558438e7dfd38eb852e2124
MD5 546f979770870a2ed706326d0945c6b3
BLAKE2b-256 7c0b07efda7a13151bf5553b333830d94cc7a4467e699d200a04497db58c3c19

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp312-cp312-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp312-cp312-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 e4b65dbff4bf33b177443ce689081f900894fb6b0016121097da10d197f49799
MD5 066da63297921fc7fc385945880478a4
BLAKE2b-256 7303071b9880434113b4ddc0c4f951836e66639cf613578eb5840bce7ee9b388

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp312-cp312-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp312-cp312-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 839bdd84d23b5bd6d702f872c2c01e649137fe9588b53cb4994e88ebc9b8d3b7
MD5 1f37b48a48357df437f03ff4617b32eb
BLAKE2b-256 7b55016d7885673542c9d75156e4b8d23fc4d364eb56ed38b7367482c58210b5

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: xcsf-1.4.7-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 631.1 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for xcsf-1.4.7-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 f482d88303cea001729863f90283d8d4976fc8a286ca840567f2b562042aa5c2
MD5 f33037f88e08dc5151de8a558b620253
BLAKE2b-256 37e678f43dc710d3b84ac84c0f9ac9e302666185b9c0b13d17f44a591678603a

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 446581613bf7360861d2b42940980a04ef4f610285a3b852ec4330ba06b81209
MD5 b1ae8f898e91f3dcdb5924d81616cb0a
BLAKE2b-256 073fd6edf7700824d4cd71bdcb7934f135ef7804f55867c0fa4ed0e972125012

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp311-cp311-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp311-cp311-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 a19c8ae662d344e547db195a2706988a870707518c3980f02834a7cc762fa919
MD5 a05e0f1ae02c21d58578c64ec1c7a84a
BLAKE2b-256 aec85317cbde6a9a0aa65db80a0c314a111f8e79c43c4000565d296a589fd10a

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp311-cp311-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp311-cp311-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 edac6c5285c1fd7c835a34eb33d47fb709798fe1b3d281d34ba9368f28956476
MD5 8584ea919450019866c8f12d4f9a4fa9
BLAKE2b-256 25bc95d3d87f73048f84d8f9055a300bfa3e633c4ff6a0b052c5dbef705392c2

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: xcsf-1.4.7-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 630.0 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for xcsf-1.4.7-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 5630ef1b71fbb0860df7b5fe966de977d0bdd0c7137d2c5c9bbcbd8fc6f3f60c
MD5 a6368f777b0bc7ded26d982cdb4595e0
BLAKE2b-256 7ccf0c355e3cea134256a6029ca665e4325ee9e460cd865daed4c425c0d98fbe

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 eb88565937edd6b1e62f6bc84d34f66a949e4defc62faa0a2e0a0d4d8f357527
MD5 17e0101d761f94ff11a4f6cb7b26f4b6
BLAKE2b-256 97f35ebae0835babdc97510d9b7f69882bf7c70deb81131bbda629e1d6d68c4f

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp310-cp310-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp310-cp310-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 7e9e32e16707e6b1e4fb23b756f560b6b4719ca43a1d1c1a56abdf0a7d90f673
MD5 087aa1a6b1bf584ae0b82379b4589c89
BLAKE2b-256 cd8e4db914feb832af5380a61638c19b47940f97163f786cc16069c862fe4387

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp310-cp310-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp310-cp310-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 57600df5c9b5dc2d4f76e33f71ec4b8bdef2fe05c21097e69973bb328491d84c
MD5 cd61c1a3ef15e457fb8fcdc10ddb5cb4
BLAKE2b-256 554e4eacb9ba0226540ac4819f1ab4f844fd5c7cb5dd5d13c1780535f86ac3f3

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: xcsf-1.4.7-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 630.3 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for xcsf-1.4.7-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 003af6b3db839a8587b7bace0d795b1d1427d36b814ebfc9e56a7e237bad3789
MD5 dee563505be782faab5b6790700b9c42
BLAKE2b-256 30988439e875fdb77661221a32ddabf7c258a010c0fff59c6717c4ce7a714b59

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b03f48469959dea7b5eeba62fb55461eee9d9141df698d866987d14137fb2ce9
MD5 54aafb71add996e7f31cba3be0c27234
BLAKE2b-256 2e81760bc738dcaac6a2a4dda71e7bb061ab485049836f424f3bf3d48b2ae4bb

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp39-cp39-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp39-cp39-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 d0b0eeea3999618082dddc2dafe12219adbbb866445b7a016789933f586ab68c
MD5 055df9e360f2ad5e9f652f357110211d
BLAKE2b-256 7b26dc8d252a01bf816b84d7cd1a1ffa1c5e6a3c49051a021e77fd98ac8f072e

See more details on using hashes here.

Provenance

File details

Details for the file xcsf-1.4.7-cp39-cp39-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for xcsf-1.4.7-cp39-cp39-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 beb8c2e0b57247b6adf2280d0294832f746a31329be6736ca581d54ee200a507
MD5 bdb9f9395340d179423094c7de681114
BLAKE2b-256 86b222e96dc93560642a514d148293811302995d68e8eedcbca7cb0e8723b485

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page