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ISMB
1993
13 years 10 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
JMLR
2008
111views more  JMLR 2008»
13 years 9 months ago
Ranking Categorical Features Using Generalization Properties
Feature ranking is a fundamental machine learning task with various applications, including feature selection and decision tree learning. We describe and analyze a new feature ran...
Sivan Sabato, Shai Shalev-Shwartz
ECCV
2002
Springer
14 years 10 months ago
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Hedvig Sidenbladh, Michael J. Black, Leonid Sigal
KDD
2009
ACM
196views Data Mining» more  KDD 2009»
14 years 3 months ago
WhereNext: a location predictor on trajectory pattern mining
The pervasiveness of mobile devices and location based services is leading to an increasing volume of mobility data. This side effect provides the opportunity for innovative meth...
Anna Monreale, Fabio Pinelli, Roberto Trasarti, Fo...
ML
2000
ACM
185views Machine Learning» more  ML 2000»
13 years 8 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