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» Results Merging Algorithm Using Multiple Regression Models
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KDD
2006
ACM
115views Data Mining» more  KDD 2006»
16 years 3 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
JMLR
2006
136views more  JMLR 2006»
15 years 2 months ago
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
Tonatiuh Peña Centeno, Neil D. Lawrence
BMCBI
2005
152views more  BMCBI 2005»
15 years 2 months ago
Improved profile HMM performance by assessment of critical algorithmic features in SAM and HMMER
Background: Profile hidden Markov model (HMM) techniques are among the most powerful methods for protein homology detection. Yet, the critical features for successful modelling ar...
Markus Wistrand, Erik L. L. Sonnhammer
JMS
2010
90views more  JMS 2010»
15 years 1 months ago
Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis
This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes ...
Kristien Van Loon, Fabián Güiza, Geert...
IJCNN
2008
IEEE
15 years 9 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...