High-accuracy document classification with a new algorithm

Küçük Resim Yok

Tarih

2018

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Inst Engineering Technology-Iet

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

A new algorithm based on learning vector quantisation classifier is presented based on a modified proximity-measure, which enforces a predetermined correct classification level in training while using sliding-mode approach for stable variation in weight updates towards convergence. The proposed algorithm and some well-known counterparts are implemented by using Python libraries and compared in a task of text classification for document categorisation. Results reveal that the new classifier is a successful contender to those algorithms in terms of testing and training performances.

Açıklama

Anahtar Kelimeler

learning (artificial intelligence), pattern classification, text analysis, high-accuracy document classification, modified proximity-measure, predetermined correct classification level, sliding-mode approach, stable variation, weight updates, Python libraries, text classification, document categorisation, learning vector quantisation classifier

Kaynak

Electronics Letters

WoS Q Değeri

Q3

Scopus Q Değeri

Q3

Cilt

54

Sayı

17

Künye