Abstract
In this paper, we focus on the problem of feature selection with confidence machines (CM). CM allows us to make predictions within predefined confidence levels, thus providing a controlled and calibrated classification environment. We present a new feature selection method, namely Strangeness Minimisation Feature Selection, designed for CM. We apply this feature selection method to the problem of microarray classification and demonstrate its effectiveness.
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References
Ambroise, C., McLachlan, G.J.: Selection bias in gene extraction on the basis of microarray gene-expression data. Proceedings of the National Academy of Sciences of the USA 99, 6562–6566 (2002)
Bellotti, T., Luo, Z., Gammerman, A., van Delft, F.W., Saha, V.: Qualified predictions for microarray and proteomics pattern diagnostics with confidence machines. International Journal of Neural Systems 15(4), 247–258 (2005)
Gammerman, A., Vovk, V.: Prediction algorithms and confidence measures based on algorithmic randomness theory. Theoretical Computer Science 287, 209–217 (2002)
Guyon, I., Weston, J., Barnhill, S., Vapnik, V.: Gene selection for cancer classification using support vector machines. Machine Learning 46, 389–422 (2002)
Luo, Z., Bellotti, T., Gammerman, A.: Qualified predictions for proteomics pattern diagnostics with confidence machines. In: Yang, Z.R., Yin, H., Everson, R.M. (eds.) IDEAL 2004. LNCS, vol. 3177, pp. 46–51. Springer, Heidelberg (2004)
Ross, M.E., Mahfouz, R., Onciu, M., Liu, H.-C., Zhou, X., Song, G., Shurtleff, S.A., Pounds, S., Cheng, C., Ma, J., Ribeiro, R.C., Rubnitz, J.E., Girtman, K., Williams, W.K., Raimondi, S.C., Liang, D.-C., Shih, L.-Y., Pui, C.-H., Downing, J.R.: Gene expression profiling of pediatric acute myelogenous leukemia. Blood 104(12), 3679–3687 (2004)
Ross, M.E., Zhou, X., Song, G., Shurtleff, S.A., Girtman, K., Williams, W.K., Liu, H.-C., Mahfouz, R., Raimondi, S.C., Lenny, N., Patel, A., Downing, J.R.: Classification of pediatric acute lymphoblastic leukemia by gene expression profiling. Blood 102, 2951–2959 (2003)
Tibshirani, R., Hastie, T., Narasimhan, B., Chu, G.: Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proceedings of the National Association of Science (USA) 99(10), 6567–6572 (2002)
Tusher, V.G., Tibshirani, R., Chu, G.: Significant analysis of microarrays applied to the ionizing radiation response. Proceedings of the National Academy of Sciences of the USA 98, 5116–5121 (2001)
van Delft, F.W., Bellotti, T., Hubank, M., Chaplin, T., Patel, N., Adamaki, M., Fletcher, D., Hann, I., Jones, L., Gammerman, A., Saha, V.: Hierarchical clustering analysis of gene expression profiles accurately identifies subtypes of acute childhood leukaemia. British Journal of Cancer 88, 54–54 (2003)
Vovk, V.: On-line confidence machines are well-calibrated. In: Proceedings of the 43rd Annual Symposium on Foundations of Computer Science, pp. 187–196. IEEE Computer Society Press, Los Alamitos (2002)
Yeoh, E.-J., Ross, M.E., Shurtleff, S.A., Williams, W.K., Patel, D., Mahfouza, R., Behm, F.G., Raimondi, S.C., Relling, M.V., Patel, A., Cheng, C., Campana, D., Wilkins, D., Zhou, X., Li, J., Liu, H., Pui, C.-H., Evans, W.E., Naeve, C., Wong, L., Downing, J.R.: Classification, subtype discovery, and prediction of outcome in pedriatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell 1, 133–143 (2002)
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Bellotti, T., Luo, Z., Gammerman, A. (2006). Strangeness Minimisation Feature Selection with Confidence Machines. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_117
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DOI: https://doi.org/10.1007/11875581_117
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45485-4
Online ISBN: 978-3-540-45487-8
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