Szczegóły publikacji
Opis bibliograficzny
Detection of atypical elements by transforming task to supervised form / Piotr KULCZYCKI, Damian Kruszewski // W: Pattern Recognition and Machine Intelligence : 7th international conference, PReMI 2017 : Kolkata, India, December 5–8, 2017 : proceedings / eds. B. Uma Shankar, [et al.]. — Switzerland : Springer, cop. 2017. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; 10597). — ISBN: 978-3-319-69899-1; e-ISBN: 978-3-319-69900-4. — S. 458–466. — Bibliogr. s. 466, Abstr. — P. Kulczyki – dod. afiliacja: Centre of Information Technology for Data Analysis Methods, Polish Academy of Sciences
Autorzy (2)
- AGHKulczycki Piotr
- Kruszewski Damian
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 119598 |
|---|---|
| Data dodania do BaDAP | 2019-04-02 |
| Tekst źródłowy | URL |
| DOI | 10.1007/978-3-319-69900-4_58 |
| Rok publikacji | 2017 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | Pattern Recognition and Machine Intelligence |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
The problem of identifying atypical elements in a data set presents many difficulties at every stage of analysis. For instance, it is not clear which traits should distinguish such elements, and what more we cannot know in advance of their natural pattern, which even if it did exist, would in its nature be significantly limited. The subject of the presented research is the procedure for transforming the problem of detection of atypical elements from an unsupervised task to a supervised one with equal-sized patterns. This allows a suitable analysis, in particular the use of diverse well-developed methods of classification. Elements are considered atypical by their rare occurrence, which when coupled with the application of nonparametric methodology enables their detection not only on the peripheries of the distribution, but also - in the multimodal case - potentially located inside.
