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Constrained Clustering: Computer Science, BIRCH (data clustering), CURE Data Clustering Algorithm
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 (Buch) |
Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!
| Lieferstatus: |
i.d.R. innert 7-14 Tagen versandfertig |
| Veröffentlichung: |
März 2026
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| Genre: |
EDV / Informatik |
| ISBN: |
9786133225848 |
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EAN-Code:
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9786133225848 |
| Verlag: |
Omniscriptum |
| Einband: |
Kartoniert |
| Sprache: |
English
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| Dimensionen: |
H 220 mm / B 150 mm / D 6 mm |
| Gewicht: |
149 gr |
| Seiten: |
88 |
| Bewertung: |
Titel bewerten / Meinung schreiben
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| Inhalt: |
| Please note that the content of this book primarily consists of articles
available from Wikipedia or other free sources online. In computer
science, constrained clustering is a class of semi-supervised learning
algorithms. Typically, constrained clustering incorporates either a set
of must-link constraints, cannot-link constraints, or both, with a Data
clustering algorithm. Both a must-link and a cannot-link constraint
define a relationship between two data instances. A must-link constraint
is used to specify that the two instances in the must-link relation
should be associated with the same cluster. A cannot-link constraint is
used to specify that the two instances in the cannot-link relation
should not be associated with the same cluster. These sets of
constraints acts as a guide for which a constrained clustering algorithm
will attempt to find clusters in a data set which satisfy the specified
must-link and cannot-link constraints. Some constrained clustering
algorithms will abort if no such clustering exists which satisfies the
specified constraints. Others will try to minimize the amount of
constraint violation should it be impossible to find a clustering which
satisfies the constraints. |
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