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» Softening Splits in Decision Trees Using Simulated Annealing
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ICANNGA
2007
Springer
100views Algorithms» more  ICANNGA 2007»
13 years 9 months ago
Softening Splits in Decision Trees Using Simulated Annealing
Predictions computed by a classification tree are usually constant on axis-parallel hyperrectangles corresponding to the leaves and have strict jumps on their boundaries. The densi...
Jakub Dvorák, Petr Savický
KDD
2007
ACM
148views Data Mining» more  KDD 2007»
14 years 5 months ago
Scalable look-ahead linear regression trees
Most decision tree algorithms base their splitting decisions on a piecewise constant model. Often these splitting algorithms are extrapolated to trees with non-constant models at ...
David S. Vogel, Ognian Asparouhov, Tobias Scheffer
CSDA
2008
128views more  CSDA 2008»
13 years 5 months ago
Classification tree analysis using TARGET
Tree models are valuable tools for predictive modeling and data mining. Traditional tree-growing methodologies such as CART are known to suffer from problems including greediness,...
J. Brian Gray, Guangzhe Fan
FLAIRS
2008
13 years 7 months ago
A Backward Adjusting Strategy and Optimization of the C4.5 Parameters to Improve C4.5's Performance
In machine learning, decision trees are employed extensively in solving classification problems. In order to design a decision tree classifier two main phases are employed. The fi...
Jason R. Beck, Maria Garcia, Mingyu Zhong, Michael...
ICRA
2002
IEEE
111views Robotics» more  ICRA 2002»
13 years 10 months ago
Feature-Based Multi-Hypothesis Localization and Tracking for Mobile Robots using Geometric Constraints
In this paper we present a new probabilistic feature-based approach to multi-hypothesis global localization and pose tracking. Hypotheses are generated using a constraintbased sea...
Kai Oliver Arras, José A. Castellanos, Rola...