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» Evaluating algorithms that learn from data streams
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201
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ICDM
2007
IEEE
136views Data Mining» more  ICDM 2007»
15 years 11 months ago
Data Discretization Unification
Data discretization is defined as a process of converting continuous data attribute values into a finite set of intervals with minimal loss of information. In this paper, we prove...
Ruoming Jin, Yuri Breitbart, Chibuike Muoh
213
Voted
BMCBI
2008
124views more  BMCBI 2008»
15 years 7 months ago
Inferring modules of functionally interacting proteins using the Bond Energy Algorithm
Background: Non-homology based methods such as phylogenetic profiles are effective for predicting functional relationships between proteins with no considerable sequence or struct...
Ryosuke Watanabe, Enrique Morett, Edgar E. Vallejo
193
Voted
ICML
2004
IEEE
16 years 8 months ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
208
Voted
ECML
2004
Springer
16 years 1 months ago
Conditional Independence Trees
It has been observed that traditional decision trees produce poor probability estimates. In many applications, however, a probability estimation tree (PET) with accurate probabilit...
Harry Zhang, Jiang Su
233
Voted
NIPS
2001
15 years 9 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr