Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
URL: https://github.com/leylabmpi/endoR/
Proper Citation: endoR (RRID:SCR_021916)
Description: Software R package to interpret fitted tree ensemble model.Used to extract and visualize how predictive variables contribute to tree ensemble model accuracy.
Resource Type: software toolkit, software resource
Defining Citation: DOI:10.1101/2022.01.03.474763
Keywords: Fitted tree ensemble model interpretation, decision ensemble, tree ensemble model accuracy, predictive variables, pairwise interactions, straightforward interpretation network
Expand AllWe found {{ ctrl2.mentions.all_count }} mentions in open access literature.
We have not found any literature mentions for this resource.
We are searching literature mentions for this resource.
Most recent articles:
{{ mention._source.dc.creators[0].familyName }} {{ mention._source.dc.creators[0].initials }}, et al. ({{ mention._source.dc.publicationYear }}) {{ mention._source.dc.title }} {{ mention._source.dc.publishers[0].name }}, {{ mention._source.dc.publishers[0].volume }}({{ mention._source.dc.publishers[0].issue }}), {{ mention._source.dc.publishers[0].pagination }}. (PMID:{{ mention._id.replace('PMID:', '') }})
A list of researchers who have used the resource and an author search tool
A list of researchers who have used the resource and an author search tool. This is available for resources that have literature mentions.
No rating or validation information has been found for endoR.
No alerts have been found for endoR.
Source: SciCrunch Registry