Association Rules represent a valid and widespread tool in data mining framework. Neverthless some important questions are still opened abput their analysis and interpretation because of the huge number of rules that is usually mined. In this paper, an integrated strategy is proposed to face all the steps of the knowledge discovery process from the extraction of the most relevant rules (Pruning) to the investigation of their common structure (Exploring) and to their graphical representation (Visualizing)
Pruning, Exploring and Visualizing Association Rules
DAVINO, CRISTINA
2000-01-01
Abstract
Association Rules represent a valid and widespread tool in data mining framework. Neverthless some important questions are still opened abput their analysis and interpretation because of the huge number of rules that is usually mined. In this paper, an integrated strategy is proposed to face all the steps of the knowledge discovery process from the extraction of the most relevant rules (Pruning) to the investigation of their common structure (Exploring) and to their graphical representation (Visualizing)File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
Pruning, Exploring and Visualizing Association Rules.pdf
accesso aperto
Tipologia:
Documento in post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza:
DRM non definito
Dimensione
954.82 kB
Formato
Adobe PDF
|
954.82 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
