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ML
2006
ACM
109views Machine Learning» more  ML 2006»
15 years 6 months ago
Cost curves: An improved method for visualizing classifier performance
Abstract This paper introduces cost curves, a graphical technique for visualizing the performance (error rate or expected cost) of 2-class classifiers over the full range of possib...
Chris Drummond, Robert C. Holte
PRL
2006
106views more  PRL 2006»
15 years 6 months ago
Invariances in kernel methods: From samples to objects
This paper presents a general method for incorporating prior knowledge into kernel methods such as Support Vector Machines. It applies when the prior knowledge can be formalized b...
Alexei Pozdnoukhov, Samy Bengio
IJISTA
2007
124views more  IJISTA 2007»
15 years 6 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
TKDE
2008
123views more  TKDE 2008»
15 years 6 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
PPSN
2010
Springer
15 years 5 months ago
Comparison-Based Optimizers Need Comparison-Based Surrogates
Abstract. Taking inspiration from approximate ranking, this paper investigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invarian...
Ilya Loshchilov, Marc Schoenauer, Michèle S...