Title: APPROCCIO DI DATA MINING BASATO SULLO STREAM MINING: UN APPROCCIO BASATO SULLO STREAM MINING PER UN AMBIENTE DINAMICO UTILIZZANDO L'ALGORITMO K-MEANS++ (Italian Edition)
Publisher: Edizioni Sapienza
Publication Date: 2024
Language: Italian
ISBN 10: 6207272315
ISBN 13: 9786207272310
Binding: Soft cover
Condition: New

About this title

Synopsis

Il clustering � una delle tecniche pi� importanti del data mining. Ha lo scopo di suddividere i dati in gruppi di oggetti simili. Questo viene definito cluster. Questa ricerca confronta l'algoritmo StreamKM++ con i lavori esistenti, come AP, IAPKM e IAPNA. L'algoritmo StreamKM++ � un nuovo algoritmo di clustering del flusso di dati e costruisce un buon clustering del flusso, utilizzando una piccola quantit� di memoria e di tempo.Molti ricercatori hanno svolto il loro lavoro con un algoritmo di clustering statico, ma in tempo reale i dati sono di natura dinamica. Come i blog, le pagine web, gli audio e i video, ecc... Per questo motivo, la tecnica statica convenzionale non supporta l'ambiente in tempo reale. In questo lavoro, viene utilizzato l'algoritmo StreamKM++ che raggiunge elevate prestazioni di clustering rispetto ai tradizionali AP, IAPKM e IAPNA. I risultati sperimentali mostrano che l'algoritmo StreamKM++ ottiene il miglior risultato rispetto ai lavori esistenti. Ha aumentato il tasso di accuratezza medio e ha ridotto il tempo di calcolo, la memoria e il numero di iterazioni.

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