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MLDM
2010
Springer
13 years 3 months ago
The Impact of Experimental Setup in Prepaid Churn Prediction for Mobile Telecommunications: What to Predict, for Whom and Does t
Prepaid customers in mobile telecommunications are not bound by a contract and can therefore change operators (`churn') at their convenience and without notification. This mak...
Dejan Radosavljevik, Peter van der Putten, Kim Kyl...
ML
2002
ACM
163views Machine Learning» more  ML 2002»
13 years 8 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
BMCBI
2007
113views more  BMCBI 2007»
13 years 8 months ago
Learning biophysically-motivated parameters for alpha helix prediction
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
14 years 2 months ago
Learning to predict train wheel failures
This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prog...
Chunsheng Yang, Sylvain Létourneau
ICML
1990
IEEE
14 years 21 days ago
Average Case Analysis of Conjunctive Learning Algorithms
We present an approach to modeling the average case behavior of learning algorithms. Our motivation is to predict the expected accuracy of learning algorithms as a function of the...
Michael J. Pazzani, Wendy Sarrett