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» Learning Nonlinear Dynamic Models from Non-sequenced Data
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CCE
2006
13 years 7 months ago
Parameter estimation in continuous-time dynamic models using principal differential analysis
Principal differential analysis (PDA) is an alternative parameter estimation technique for differential equation models in which basis functions (e.g., B-splines) are fitted to dy...
A. A. Poyton, M. S. Varziri, K. B. McAuley, P. J. ...
ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
14 years 1 months ago
Mining Complex Time-Series Data by Learning Markovian Models
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
ICDM
2003
IEEE
119views Data Mining» more  ICDM 2003»
14 years 27 days ago
A Dynamic Adaptive Self-Organising Hybrid Model for Text Clustering
Clustering by document concepts is a powerful way of retrieving information from a large number of documents. This task in general does not make any assumption on the data distrib...
Chihli Hung, Stefan Wermter
BMCBI
2010
160views more  BMCBI 2010»
13 years 7 months ago
Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53
Background: The availability of various "omics" datasets creates a prospect of performing the study of genomewide genetic regulatory networks. However, one of the major ...
Junbai Wang, Tianhai Tian
ESANN
2006
13 years 9 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...