"2006-09-04+02:00"^^ . . "3"^^ . "Compared is new neural network based clustering method with some comertionally available in statistical packages. The experimental results of the analysis of different data sets by the neural network method show that this method provides reasonable results compared with traditional attempts or their combination. The advantage of the neural method is its' less complicated usage and better scalability. We propose that they outperform traditional methods when applied to large data sets with high dimensionality." . "88-89744-01-4" . . . "RIV/67985807:_____/06:00079194!RIV07-AV0-67985807" . "H\u00FAsek, Du\u0161an" . . . "Overlapping Clustering of Binary Variables" . . "\u0158ezankov\u00E1, H." . . "[0D60C477E900]" . "7"^^ . . "P\u0159ekr\u00FDvaj\u00EDc\u00ED se shlukov\u00E1n\u00ED bin\u00E1rn\u00EDch prom\u011Bnn\u00FDch"@cs . . "Overlapping Clustering of Binary Variables"@en . "RIV/67985807:_____/06:00079194" . . "491258" . . . "Anacapri" . "TILAPIA Edizioni" . . . "Overlapping Clustering of Binary Variables"@en . "P\u0159ekr\u00FDvaj\u00EDc\u00ED se shlukov\u00E1n\u00ED bin\u00E1rn\u00EDch prom\u011Bnn\u00FDch"@cs . "1;7" . . . "Napoli" . . . . . "Overlapping Clustering of Binary Variables" . "Knowledge Extraction and Modelling" . "Porovn\u00E1n je nov\u00FD, na neuronov\u00E9m paradigmatu zalo\u017Een\u00FD, algoritmus pro shlukovou anal\u00FDzu (NBFA) s n\u011Bkter\u00FDmi komer\u010Dn\u011B dostupn\u00FDmi.Experiment\u00E1ln\u00ED v\u00FDsledky uk\u00E1zaly v\u00FDhodnost pou\u017Eit\u00ED neuronov\u00E9ho algoritmu, kv\u016Fli jeho lep\u0161\u00ED \u0161k\u00E1lovatelnosti, zejm\u00E9na v p\u0159\u00EDpad\u011B rozs\u00E1hl\u00FDch datov\u00FDch soubor\u016F s velkou dimenzionalitou."@cs . "Compared is new neural network based clustering method with some comertionally available in statistical packages. The experimental results of the analysis of different data sets by the neural network method show that this method provides reasonable results compared with traditional attempts or their combination. The advantage of the neural method is its' less complicated usage and better scalability. We propose that they outperform traditional methods when applied to large data sets with high dimensionality."@en . "P(1ET100300414), P(GA201/05/0079), Z(AV0Z10300504)" . . "machine learning; knowledge extraction; overlapping clustering; clustering of variables; fuzzy cluster analysis; factor analysis; neural newtorks"@en . "Frolov, A. A." . . "1"^^ . .