- Titel
- An Approach to Incremental Learning Good Classification Tests
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa-113159
- Quellenangabe
- Cellier, Peggy, Distel, Felix und Ganter, Bernhard (Hrsg.): Contributions to the 11th International Conference on Formal Concept Analysis, 2013, S. 51-64
- Quellenangabe
- Contributions to the 11th International Conference on Formal Concept Analysis
- Abstract (EN)
- An algorithm of incremental mining implicative logical rules is pro-posed. This algorithm is based on constructing good classification tests. The in-cremental approach to constructing these rules allows revealing the interde-pendence between two fundamental components of human thinking: pattern recognition and knowledge acquisition.
- Freie Schlagwörter (DE)
- inkrementales Lernen, Klassifikationstest, Mustererkennung, maschinelles Lernen, Wissenserwerb
- Freie Schlagwörter (EN)
- Incremental learning, Good classification test, Pattern recognition, Machine learning, Human mental operations
- Klassifikation (DDC)
- 004
- Klassifikation (RVK)
- ST 278, ST 125
- Publizierende Institution
- Technische Universität Dresden, Dresden
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa-113159
- Veröffentlichungsdatum Qucosa
- 28.05.2013
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
