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MCS
2000
Springer
15 years 7 months ago
Ensemble Methods in Machine Learning
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
Thomas G. Dietterich
137
Voted
CORR
2008
Springer
158views Education» more  CORR 2008»
15 years 3 months ago
Improved Smoothed Analysis of the k-Means Method
The k-means method is a widely used clustering algorithm. One of its distinguished features is its speed in practice. Its worst-case running-time, however, is exponential, leaving...
Bodo Manthey, Heiko Röglin
CVPR
2005
IEEE
16 years 5 months ago
The Modified pbM-Estimator Method and a Runtime Analysis Technique for the RANSAC Family
Robust regression techniques are used today in many computer vision algorithms. Chen and Meer recently presented a new robust regression technique named the projection based M-est...
Stas Rozenfeld, Ilan Shimshoni
117
Voted
AUSDM
2007
Springer
100views Data Mining» more  AUSDM 2007»
15 years 9 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
105
Voted
ICIAP
2007
ACM
16 years 3 months ago
A Method of Clustering Combination Applied to Satellite Image Analysis
An algorithm for combining results of different clusterings is presented in this paper, the objective of which is to find groups of patterns which are common to all clusterings. T...
Ivan O. Kyrgyzov, Henri Maître, Marine Campe...