A Clustering Rule Based Approach for Classification Problems

Predictive models, such as rule based classifiers, often have difficulty with incomplete data (e.g., erroneous/missing values). So, this work presents a technique used to reduce the severity of the effects of missing data on the performance of rule base classifiers using divisive data clustering. Th...

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Veröffentlicht in:	International journal of data warehousing and mining 2012-01, Vol.8 (1), p.1-23
Hauptverfasser:	Williams, Philicity K, Soares, Caio V, Gilbert, Juan E
Format:	Artikel
Sprache:	eng
Schlagworte:	Analysis Classification Classifiers Cluster analysis Clustering Clusters Construction Data warehousing Missing data Model testing Prediction models Rule based
Online-Zugang:	Volltext
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