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Weka (z angl. Waikato Environment for Knowledge Analysis, waikatské prostředí pro analýzu znalostí) je populární balík programů strojového učení napsaný v Javě, vyvinutý na University of Waikato, Nový Zéland. Weka je svobodný software dostupný podle GNU General Public License.
Související články & Overview
Explore the main themes, entities and connections around Weka. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
waikato datové datasetem uci učení university of gnu general public license javě analýzu oknem exploreru otevřeným iris položky popis arff
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Weka | Aktuální verze | 3.8.3 (4. 9. 2018) | 1.00 | infobox |
| Weka | Licence | GNU General Public License | 1.00 | infobox |
| Weka | Operační systém | multiplatformní | 1.00 | infobox |
| Weka | Platforma | Java Virtual Machine | 1.00 | infobox |
| Weka | Typ softwaru | strojové učení | 1.00 | infobox |
| Weka | Vyvíjeno v | Java | 1.00 | infobox |
| Weka | Vývojář | University of Waikato | 1.00 | infobox |
| Weka | Web | http://www.cs.waikato.ac.nz/~ml/weka/ | 1.00 | infobox |
| Weka | related to Externí odkazy | Obrázky | 0.60 | section |
| Weka | related to Externí odkazy | Wikimedia Commons | 0.60 | section |
| Weka | related to Reference | Wikipedii | 0.60 | section |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.