Abstract
The use of artificial outputs generated by a classifier simulator has recently emerged as a new trend to provide an underlying evaluation of classifier combination methods. In this paper, we propose a new method for the artificial generation of classifier outputs based on additional parameters which provide sufficient diversity to simulate, for a problem of any number of classes and any type of output, any classifier performance. This is achieved through a two-step algorithm which first builds a confusion matrix according to desired behaviour and secondly generates, from this confusion matrix, outputs of any specified type. We provide the detailed algorithms and constraints to respect for the construction of the matrix and the generation of outputs. We illustrate on a small example the usefulness of the classifier simulator.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Duin, R.P.W., Tax, D.M.J.: Experiments With Classifier Combining Rules. In Proc. First Int. Workshop On Multiple Classifier System, MCS 2000, Vol. 1857, Springer, Berlin, (2000) 16–29
Ho, T.K., Hull, J.J., Srihari, S.N.: Decision Combination In Multiple Classifier Systems. IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol.16, No. 1, (1994) 66–75
Impedovo, S., Salzo, A.: Evaluation Of Combination Methods. Proc. ICDAR, Bangalore, India, (1999) 394–397
Kittler, J., Hatef, M., Duin, R.P.W., Matas, J.: On Combining Classifiers. IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 20, No. 3 (1998)
Kuncheva, L.I., Kountchev, R.K.: Generating Classifier Outputs Of Fixed Accuracy And Diversity. Pattern Recognition Letters, Vol. 23. (2002) 593–600
Lecce, V.D., Dimauro, G., Guerrierro, A., Impedovo, S., Pirlo, G., Salzo, A.: Classifier Combination: The Role Of A-Priori Knowledge. In Proc. Of The 7th International Workshop On Frontiers In Handwriting Recognition, Amsterdam, The Netherlands (2000) 143–152
Parker, J.R.: Rank And Response Combination From Confusion Matrix Data. Information Fusion, Vol. 2. (2001) 113–120
Roli, F., Fumera, G., Kittler, J.: Fixed And Trained Combiners For Fusion Of Imbalanced Pattern Classifiers. The Fifth International Conference On Information Fusion, Annapolis (Washington) USA (2002)
Tax, D.M.J., Breukelen, M.V., Duin, R.P.W., Kittler, J.: Combining Multiple Classifiers By Averaging Or By Multiplying ?. Pattern Recognition, Vol. 33. (2000) 1475–1485
Van Erp, M., Vuurpijl, L., Schomaker, L.: An Overview And Comparison Of Voting Methods For Pattern Recognition. 8th International Workshop On Frontiers In Handwriting Recognition, Niagara-on-the-Lake, Ontario, (2002) 195–200
Xiao, B.H., Wang, C.H., Dai, R.W.: Adaptive Combination Of Classifiers And Its Application To Handwritten Chinese Character Recognition. In Proc. ICPR, Barcelona, Spain, Vol. 2. (2000) 2327–2330
Xu, L., Krzyzak, A., Suen, C.Y.: Methods Of Combining Multiple Classifiers And Their Applications To Handwriting Recognition. IEEE Transaction On Systems, Man, and Cybernetics, Vol. 22. No 3 (1992) 418–435
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zouari, H., Heutte, L., Lecourtier, Y., Alimi, A. (2003). Simulating Classifier Outputs for Evaluating Parallel Combination Methods. In: Windeatt, T., Roli, F. (eds) Multiple Classifier Systems. MCS 2003. Lecture Notes in Computer Science, vol 2709. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44938-8_30
Download citation
DOI: https://doi.org/10.1007/3-540-44938-8_30
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40369-2
Online ISBN: 978-3-540-44938-6
eBook Packages: Springer Book Archive