URL: https://xgboost.ai/
Proper Citation: XGBoost (RRID:SCR_021361)
Description: Open source software tool as library for implementation of gradient boosting with various machine learning algorithms.Optimized distributed gradient boosting library designed to be highly efficient, flexible and portable.Supports regression, classification, ranking and user defined objectives.
Synonyms: eXtreme Gradient Boosting
Resource Type: software resource, software library, software toolkit
Defining Citation: DOI:10.1145/2939672.2939785
Keywords: Machine learning, gradient boosting, supports regression, supports classification, supports ranking, tree boosting system
Expand AllWe found {{ ctrl2.mentions.total_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 XGBoost.
No alerts have been found for XGBoost.
Source: SciCrunch Registry