Unsupervised learning in latent space with a fuzzy logic guided modified ba
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RIS BIB ENDNOTEUnsupervised learning in latent space with a fuzzy logic guided modified ba
Data publikacji: 29.08.2018
Czasopismo Techniczne, 2018, Volume 8 Year 2018 (115), s. 141 - 153
https://doi.org/10.4467/2353737XCT.18.121.8896Autorzy
Unsupervised learning in latent space with a fuzzy logic guided modified ba
W publikacji zmodyfikowany algorytm nietoperzowy z rozmytym kontrolerem typu mamdaniego został zastosowany do problemu analizy skupisk dla danych tekstowych. Proces uczenia odbywa się w przestrzeni skompresowanej, otrzymanej z dekompozycji svD zbioru uczącego. Prezentowany algorytm uczy się jednocześnie optymalnego pokrycia klastrami przestrzeni oraz liczebności klastrów. Do oceny jakości rozwiązania zastosowano wskaźnik sillhouette. Dane w reprezentacji wektorowej otrzymano z wykorzystaniem transformacji Tf-IDf. Prezentowany algorytm przetestowana na zbiorze „20 newsgroup”.
In this paper, a modified bat algorithm with fuzzy inference Mamdani-type system is applied to the problem of document clustering in a semantic features space induced by SV D decomposition. The algorithm learns the optimal clustering of the documents as well as the optimal number of clusters in a concept space; thus, making it suitable for a large and spare dataset which occur in information retrieval system. A centroidbased solution in multidimensional space is evaluated with a silhouette index. A TF-IDF method is used to represent documents in vector space. The presented algorithm is tested on the 20 Newsgroup dataset.
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Informacje: Czasopismo Techniczne, 2018, Volume 8 Year 2018 (115), s. 141 - 153
Typ artykułu: Oryginalny artykuł naukowy
Tytuły:
Unsupervised learning in latent space with a fuzzy logic guided modified ba
Unsupervised learning in latent space with a fuzzy logic guided modified ba
Studium Doktoranckie, Instytut Badań Systemowych, Polska Akademia Nauk
Publikacja: 29.08.2018
Status artykułu: Otwarte
Licencja: Żadna
Udział procentowy autorów:
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