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ECML
2003
Springer
13 years 10 months ago
Logistic Model Trees
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Niels Landwehr, Mark Hall, Eibe Frank
DSOM
2000
Springer
13 years 10 months ago
Operational Data Analysis: Improved Predictions Using Multi-computer Pattern Detection
Operational Data Analysis (ODA) automatically 1) monitors the performance of a computer through time, 2) stores such information in a data repository, 3) applies data-mining techn...
Ricardo Vilalta, Chidanand Apté, Sholom M. ...
IWPSE
2007
IEEE
13 years 11 months ago
Improving defect prediction using temporal features and non linear models
Predicting the defects in the next release of a large software system is a very valuable asset for the project manger to plan her resources. In this paper we argue that temporal f...
Abraham Bernstein, Jayalath Ekanayake, Martin Pinz...
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 3 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava
NN
2006
Springer
114views Neural Networks» more  NN 2006»
13 years 5 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek