Skip to main content

FAME3R: a re-implementation of the FAME3 model

Project description

FAME3R: a re-implementation of the FAME3 model.

Installation

  1. Create a conda environment with the required python version:
conda create --name fame3r-env python=3.10
  1. Activate the environment:
conda activate fame3r-env
  1. Install package:
pip install fame3r

Usage

Determining the optimal hyperparameters via k-fold cross-validation

fame3r-cv-hp-search -i INPUT_FILE -o OUTPUT_FOLDER -r RADIUS[OPTIONAL, DEFAULT=5] -n NUMFOLDS[OPTIONAL, DEFAULT=10]

Training a model

fame3r-train -i INPUT_FILE -o OUTPUT_FOLDER -r RADIUS[OPTIONAL, DEFAULT=5]

Applying a trained model on some (labeled) test data

fame3r-test -i INPUT_FILE -m MODEL_FILE -o OUTPUT_FOLDER -r RADIUS[OPTIONAL, DEFAULT=5] -t THRESHOLD[OPTIONAL, DEFAULT=0.2]

Computing the SoMs of some unlabeled data

fame3r-infer -i INPUT_FILE -m MODEL_FILE -o OUTPUT_FOLDER -r RADIUS[OPTIONAL, DEFAULT=5] -t THRESHOLD[OPTIONAL, DEFAULT=0.2]

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

fame3r-0.0.2.tar.gz (9.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fame3r-0.0.2-py3-none-any.whl (14.0 kB view details)

Uploaded Python 3

File details

Details for the file fame3r-0.0.2.tar.gz.

File metadata

  • Download URL: fame3r-0.0.2.tar.gz
  • Upload date:
  • Size: 9.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.16

File hashes

Hashes for fame3r-0.0.2.tar.gz
Algorithm Hash digest
SHA256 534ad64f7c6d57c39e8dcd8381fdaca4295923cc4362a3df92c54fbd54788ff6
MD5 310e15d45ea1cff0e5b9301717f354f0
BLAKE2b-256 15c621c5cd05157dc0d1b08176869834610d25a9f8fd4df9d59accea68f831f2

See more details on using hashes here.

File details

Details for the file fame3r-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: fame3r-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 14.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.16

File hashes

Hashes for fame3r-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 5a540be0f75d7f82f1b96fe8c6db49f2395693af39a8e484951150cdd0e8c10d
MD5 815edf9aa5cae6b03dad1d8711015422
BLAKE2b-256 468429e2e63ac425b14e9e5c983d5f099983d233b9434cba3dc2b917a1b6beb6

See more details on using hashes here.

Supported by

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