July 2017
Intermediate to advanced
378 pages
10h 44m
German
Content preview from Einführung in Machine Learning mit Python
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Hierarchisches Clustering und Dendrogramme
Das Ergebnis beim agglomerativen Clustering ist ein sogenanntes hierarchisches Clustering. Das Clusterverfahren arbeitet iterativ, sodass jeder Punkt eine Reise vom anfänglichen Ein-Punkt-Cluster bis zu seinem endgültigen Cluster durchlebt. Jeder Zwischenschritt ist eine gültige Zuordnung (einer anderen Anzahl) von Clustern. Manchmal ist es hilfreich, sich alle möglichen Cluster auf einmal anzusehen. Das nächste Beispiel (Abbildung 3-35) zeigt eine Überlagerung aller möglichen Clusterzuordnungen in Abbildung 3-33. Dies gibt uns Aufschluss darüber, wie sich jeder Cluster aus kleineren Clustern zusammensetzt:
In[61]:
mglearn.plots.plot_agglomerative()
Abbildung 3-35: Über agglomeratives Clustering erzeugte ...
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