PyGOP: A Python library for Generalized Operational Perceptron algorithms

Tutkimustuotos: ArtikkeliScientificvertaisarvioitu

10 Sitaatiot (Scopus)

Abstrakti

PyGOP provides a reference implementation of existing algorithms using Generalized Operational Perceptron (GOP), a recently proposed artificial neuron model. The implementation adopts a user-friendly interface while allowing a high level of customization including user-defined operators, custom loss function, custom metric functions that requires full batch evaluation such as Precision, Recall or F1. Besides, PyGOP supports different computation environments (CPU/GPU) on both single machine and cluster using SLURM job scheduler. In addition, since training GOP-based algorithms might take days, PyGOP automatically saves checkpoints during computation and allows resuming to the last checkpoint in case the script got interfered in the middle during the progression.

AlkuperäiskieliEnglanti
Artikkeli104801
JulkaisuKnowledge-Based Systems
Vuosikerta182
DOI - pysyväislinkit
TilaJulkaistu - 2019
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Software
  • Management Information Systems
  • Information Systems and Management
  • Artificial Intelligence

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