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GitHub / jrudar / LANDMark
Implementation of a decision tree ensemble which splits each node using learned linear and non-linear functions.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jrudar%2FLANDMark
Stars: 5
Forks: 3
Open Issues: 0
License: mit
Language: Jupyter Notebook
Repo Size: 862 KB
Dependencies:
19
Created: almost 3 years ago
Updated: about 1 month ago
Last pushed: about 1 month ago
Last synced: about 1 month ago
Commit Stats
Commits: 128
Authors: 4
Mean commits per author: 32.0
Development Distribution Score: 0.391
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/jrudar/LANDMark
Topics: bioinformatics, classifier-ensembles, ecology-modelling, machine-learning
Files
Dependencies
- actions/checkout v2 composite
- conda-incubator/setup-miniconda v2 composite
- actions/checkout v3 composite
- actions/setup-python v3 composite
- pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite