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» Decision trees do not generalize to new variations
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PRICAI
2000
Springer
14 years 4 days ago
The Lumberjack Algorithm for Learning Linked Decision Forests
While the decision tree is an effective representation that has been used in many domains, a tree can often encode a concept inefficiently. This happens when the tree has to repres...
William T. B. Uther, Manuela M. Veloso
ACCV
2010
Springer
13 years 3 months ago
Face Recognition with Decision Tree-Based Local Binary Patterns
Many state-of-the-art face recognition algorithms use image descriptors based on features known as Local Binary Patterns (LBPs). While many variations of LBP exist, so far none of ...
Daniel Maturana, Domingo Mery, Alvaro Soto
ML
2008
ACM
135views Machine Learning» more  ML 2008»
13 years 8 months ago
Compiling pattern matching to good decision trees
We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decis...
Luc Maranget
KI
2002
Springer
13 years 8 months ago
Incremental Fuzzy Decision Trees
Abstract. We present a new classification algorithm that combines three properties: It generates decision trees, which proved a valuable and intelligible tool for classification an...
Marina Guetova, Steffen Hölldobler, Hans-Pete...
GECCO
2004
Springer
14 years 2 months ago
Dynamic Limits for Bloat Control: Variations on Size and Depth
Abstract. We present two important variations on a recently successful bloat control technique, Dynamic Maximum Tree Depth, intended at further improving the results and extending ...
Sara Silva, Ernesto Costa