← Search

Data · dataset · 2022

fseval - A Benchmarking Framework for Feature Selection and Feature Ranking Algorithms

Listed in IISH Dataverse

The fseval Python package allows benchmarking Feature Selection and Feature Ranking algorithms on a large scale, and facilitates the comparison of multiple algorithms in a systematic way.

Description

In particular, fseval enables users to run experiments in parallel and distributed over multiple machines, and export the results to an SQL database. The execution of an experiment can be fully determined by a configuration file, which means the experiment results can be reproduced easily, given only the configuration file. fseval has high test coverage, continuous integration, and rich documentation.

The package is open source and can be installed through PyPI.

Links

Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
IISH Dataversedoi:10.34894/KDEPR012 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].dataverse_subject:computer-and-information-sciencesource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
concepts[field].local:field:computer-science-aimapping · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
created_datesource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0
descriptionsource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/description
publication_datesource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0
titlesource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/name
updated_datesource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0
version_labelsource · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0