Local Pattern Detection: International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
jul. 2005 · Springer
E-bog
233
Sider
reportBedømmelser og anmeldelser verificeres ikke Få flere oplysninger
Om denne e-bog
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new ?eld knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the ?eld o?ers the opportunity to combine the expertise of di?erent ?elds intoacommonobjective.Moreover,withineach?elddiversemethodshave been developed and justi?ed with respect to di?erent quality criteria. We have toinvestigatehowthesemethods cancontributeto solvingthe problemofKDD. Traditionally, KDD was seeking to ?nd global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to ?nd only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new ?eld of local patterns.
Bedøm denne e-bog
Fortæl os, hvad du mener.
Oplysninger om læsning
Smartphones og tablets
Installer appen Google Play Bøger til Android og iPad/iPhone. Den synkroniserer automatisk med din konto og giver dig mulighed for at læse online eller offline, uanset hvor du er.
Bærbare og stationære computere
Du kan høre lydbøger, du har købt i Google Play via browseren på din computer.
e-læsere og andre enheder
Hvis du vil læse på e-ink-enheder som f.eks. Kobo-e-læsere, skal du downloade en fil og overføre den til din enhed. Følg den detaljerede vejledning i Hjælp for at overføre filerne til understøttede e-læsere.
