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IJCAI
2007
14 years 11 months ago
Extracting Propositional Rules from Feed-forward Neural Networks - A New Decompositional Approach
In this paper, we present a new decompositional approach for the extraction of propositional rules from feed-forward neural networks of binary threshold units. After decomposing t...
Sebastian Bader, Steffen Hölldobler, Valentin...
CC
2007
Springer
208views System Software» more  CC 2007»
15 years 4 months ago
A New Elimination-Based Data Flow Analysis Framework Using Annotated Decomposition Trees
Abstract. We introduce a new framework for elimination-based data flow analysis. We present a simple algorithm and a delayed algorithm that exhibit a worstcase complexity of O(n2 ...
Bernhard Scholz, Johann Blieberger
ICIAR
2005
Springer
15 years 3 months ago
Compressing 2-D Shapes Using Concavity Trees
Concavity trees have been known for quite some time as structural descriptors of 2-D shape; however, they haven’t been explored further until recently. This paper shows how 2-D s...
Ossama El Badawy, Mohamed S. Kamel
COMSIS
2006
156views more  COMSIS 2006»
14 years 10 months ago
A Comparison of the Bagging and the Boosting Methods Using the Decision Trees Classifiers
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
Kristína Machova, Miroslav Puszta, Frantise...
KDD
2003
ACM
150views Data Mining» more  KDD 2003»
15 years 10 months ago
Learning relational probability trees
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...