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» Second Tier for Decision Trees
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KDD
2000
ACM
121views Data Mining» more  KDD 2000»
13 years 11 months ago
Mining high-speed data streams
Many organizations today have more than very large databases; they have databases that grow without limit at a rate of several million records per day. Mining these continuous dat...
Pedro Domingos, Geoff Hulten
CIMCA
2008
IEEE
14 years 1 months ago
Tree Exploration for Bayesian RL Exploration
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Christos Dimitrakakis
ECAI
2004
Springer
14 years 23 days ago
Local Search for Heuristic Guidance in Tree Search
Recent work has shown the promise in using local-search “probes” as a basis for directing a backtracking-based refinement search. In this approach, the decision about the next...
Alexander Nareyek, Stephen F. Smith, Christian M. ...
ML
2000
ACM
185views Machine Learning» more  ML 2000»
13 years 7 months ago
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of classification accuracy, training time, and (in the ca...
Tjen-Sien Lim, Wei-Yin Loh, Yu-Shan Shih
ISSAC
1995
Springer
155views Mathematics» more  ISSAC 1995»
13 years 11 months ago
On the Implementation of Dynamic Evaluation
Dynamic evaluation is a technique for producing multiple results according to a decision tree which evolves with program execution. Sometimes it is desired to produce results for ...
Peter A. Broadbery, T. Gómez-Díaz, S...