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ICMLA
2008
15 years 5 months ago
Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
Cecilia Sönströd, Ulf Johansson, Ulf Nor...
TKDE
2008
128views more  TKDE 2008»
15 years 4 months ago
Using Context to Improve Predictive Modeling of Customers in Personalization Applications
The idea that context is important when predicting customer behavior has been maintained by scholars in marketing and data mining. However, no systematic study measuring how much t...
Cosimo Palmisano, Alexander Tuzhilin, Michele Gorg...
ESANN
2007
15 years 5 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
ICML
2007
IEEE
16 years 4 months ago
An integrated approach to feature invention and model construction for drug activity prediction
We present a new machine learning approach for 3D-QSAR, the task of predicting binding affinities of molecules to target proteins based on 3D structure. Our approach predicts bind...
David Page, Jesse Davis, Soumya Ray, Vítor ...
AUSDM
2007
Springer
100views Data Mining» more  AUSDM 2007»
15 years 10 months ago
Predictive Model of Insolvency Risk for Australian Corporations
This paper describes the development of a predictive model for corporate insolvency risk in Australia. The model building methodology is empirical with out-ofsample future year te...
Rohan A. Baxter, Mark Gawler, Russell Ang