URL: http://www.cs.waikato.ac.nz/ml/weka/
Proper Citation: Weka (RRID:SCR_001214)
Description: A collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
Abbreviations: Weka
Synonyms: Weka 3: Data Mining Software in Java, WEKA Data Mining Software
Resource Type: software resource, data processing software, software application, text-mining software
Defining Citation: PMID:15073010
Keywords: data mining, java, machine learning, pre-processing, classification, regression, clustering, feature selection, visualization
Expand Allhas parent organization |
We 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 Weka.
No alerts have been found for Weka.
Source: SciCrunch Registry