FCA basic algorithms
Project description
FCA utils
Module for FCA basics such as retrieving concepts, drawing a hasse diagram, etc
Getting formal concepts
from base_models import Context
from get_lattice import Inclose
c = Context(O, A, I)
concepts = Inclose().get_concepts(c)
Getting association rules
from base_models import Context
from get_lattice import Inclose
c = Context(O, A, I)
Inclose().get_association_rules(c, min_support=0.4, min_confidence=1)
Drawing hasse diagram
from get_lattice import Inclose
from plot.plot import plot_from_hasse
from base_models import Context
c = Context(O, A, I)
hasse_lattice, concepts = Inclose().get_lattice(c)
plot_from_hasse(hasse_lattice, concepts)
TODO
- Make algorithms to be able to work with streams (big files)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
File details
Details for the file fca_algorithms-0.0.1-py3-none-any.whl
.
File metadata
- Download URL: fca_algorithms-0.0.1-py3-none-any.whl
- Upload date:
- Size: 16.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3c405444214e05aca6f9ed5ef0a5cdbcef7dffece5049c37d9919f17b3444a9e |
|
MD5 | eb7b97b9f861f713547356d83ab04895 |
|
BLAKE2b-256 | 4e0a17cddcecae93c1728e79980b408f8cbab398713b372ef6fe3409d7dc0d7a |