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Classificazione degli URL dannosi

Classificazione degli URL dannosi


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International Edition


About the Book

Questo libro si propone di sviluppare un modello che classifichi se un determinato sito web è legittimo o dannoso utilizzando metodologie di apprendimento automatico e di determinare se l'aumento del set di caratteristiche di un modello porti a un aumento delle sue prestazioni. Gli autori hanno utilizzato tre casi distinti per generare un modello ottimale, ognuno dei quali si differenzia per il numero di caratteristiche utilizzate nel set di dati. Il primo caso ha utilizzato il dataset di base o originale. Il secondo caso ha utilizzato un set di caratteristiche esteso. L'algoritmo di selezione delle caratteristiche è stato utilizzato nel set di caratteristiche esteso per creare un nuovo set di dati per il terzo caso. I classificatori utilizzati per generare i modelli sono Random Forest, J48, C-SVC e kNN. Il risultato ha mostrato un aumento delle prestazioni quando si confrontano i modelli del primo caso con quelli del secondo. Non sono stati osservati cambiamenti significativi quando i modelli del secondo caso sono stati confrontati con quelli del terzo. Lo studio ha dimostrato che esiste una relazione direttamente proporzionale tra il numero di caratteristiche di un modello e le sue prestazioni. L'ampliamento del numero di caratteristiche del set di dati porta a un aumento delle prestazioni di ciascun modello.


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Product Details
  • ISBN-13: 9786205307441
  • Publisher: KS Omniscriptum Publishing
  • Publisher Imprint: Edizioni Sapienza
  • Height: 229 mm
  • No of Pages: 176
  • Spine Width: 10 mm
  • Width: 152 mm
  • ISBN-10: 6205307448
  • Publisher Date: 04 Nov 2022
  • Binding: Paperback
  • Language: Italian
  • Returnable: N
  • Weight: 317 gr


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