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PKDD
2004
Springer
324views Data Mining» more  PKDD 2004»
15 years 11 months ago
Orange: From Experimental Machine Learning to Interactive Data Mining
Abstract. Orange (www.ailab.si/orange) is a suite for machine learning and data mining. It can be used though scripting in Python or with visual programming in Orange Canvas using ...
Janez Demsar, Blaz Zupan, Gregor Leban, Tomaz Curk
FGCS
2007
106views more  FGCS 2007»
15 years 5 months ago
Distributed data mining services leveraging WSRF
The continuous increase of data volumes available from many sources raises new challenges for their effective understanding. Knowledge discovery in large data repositories involv...
Antonio Congiusta, Domenico Talia, Paolo Trunfio
KDD
1998
ACM
136views Data Mining» more  KDD 1998»
15 years 10 months ago
Integrating Classification and Association Rule Mining
Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the dat...
Bing Liu, Wynne Hsu, Yiming Ma
PAKDD
2009
ACM
87views Data Mining» more  PAKDD 2009»
16 years 17 days ago
Application-Independent Feature Construction from Noisy Samples
When training classifiers, presence of noise can severely harm their performance. In this paper, we focus on “non-class” attribute noise and we consider how a frequent fault-t...
Dominique Gay, Nazha Selmaoui, Jean-Françoi...
ICDM
2005
IEEE
130views Data Mining» more  ICDM 2005»
15 years 11 months ago
Obtaining Best Parameter Values for Accurate Classification
In this paper we examine the effect that the choice of support and confidence thresholds has on the accuracy of classifiers obtained by Classification Association Rule Mining. ...
Frans Coenen, Paul H. Leng