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  1. 2019
  2. Published

    Distribution Calibration for Regression

    Song, H., Diethe, T., Kull, M. & Flach, P., 15 May 2019, International Conference on Machine Learning, 9-15 June 2019, Long Beach, California, USA. Chaudhuri, K. & Salakhutdinov, R. (eds.). Proceedings of Machine Learning Research, p. 5897-5906 10 p. (Proceedings of Machine Learning Research; vol. 97).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  3. 2018
  4. Published

    Releasing eHealth analytics into the wild: Lessons learnt from the SPHERE project

    Diethe, T., Nieto, M. P., Tonkin, E., Holmes, M., Sokol, K., Twomey, N., Kull, M., Song, H. & Flach, P., 19 Jul 2018, KDD'18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery (ACM), p. 243-252 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  5. Published

    Analysis of patient domestic activity in recovery from hip or knee replacement surgery: modelling wrist-worn wearable RSSI and accelerometer data in the wild

    Holmes, M., Song, H., Tonkin, E. L., Perello Nieto, M., Grant, S. & Flach, P., 13 Jul 2018, Proceedings of the 3rd International Workshop on Knowledge Discovery in Healthcare Data: co-located with the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018). CEUR Workshop Proceedings, p. 13-20 8 p. (CEUR Workshop Proceedings; vol. 2148).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  6. In preparation

    Non-Parametric Calibration of Probabilistic Regression

    Song, H., Flach, P. & Kull, M., 2018, (In preparation).

    Research output: Working paperWorking paper and Preprints

  7. 2017
  8. Published

    Beyond Sigmoids: How to obtain well-calibrated probabilities from binary classifiers with beta calibration

    Kull, M., Silva Filho, T. M. & Flach, P., 15 Dec 2017, In : Electronic Journal of Statistics. 11, 2, p. 5052-5080 29 p.

    Research output: Contribution to journalArticle

  9. Published

    CASP-DM: Context Aware Standard Process for Data Mining

    Martínez-Plumed, F., Contreras-Ochando, L., Ferri, C., Flach, P., Hernández-Orallo, J., Kull, M., Lachiche, N. & Ramírez-Quintana, M. J., 19 Sep 2017, In : arXiv. 38 p.

    Research output: Contribution to journalArticle

  10. Published

    Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers

    Kull, M., De Menezes E Silva Filho, T. & Flach, P., 1 Apr 2017, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017). Journal of Machine Learning Research, 9 p. (JMLR Workshop and Conference Proceedings; vol. 54).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  11. Published

    Background Check: A General Technique to Build More Reliable and Versatile Classifiers

    Perello-Nieto, M., Filho, T. M. S., Kull, M. & Flach, P., Mar 2017, 2016 IEEE 16th International Conference on Data Mining (ICDM 2016): Proceedings of a meeting held 12-15 December 2016, Barcelona, Spain. Institute of Electrical and Electronics Engineers (IEEE), p. 1143-1148 6 p. 7837963. (Proceedings of the IEEE International Conference on Data Mining (ICDM)).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  12. 2016
  13. Published

    Reframing in context: A systematic approach for model reuse in machine learning

    Hernández-Orallo, J., Martinez-Uso, A., B.C. Prudencio, R., Kull, M., Flach, P. A., Ahmed, C. F. & Lachiche, N., 15 Nov 2016, In : AI Communications. 29, 5, p. 551-566 16 p.

    Research output: Contribution to journalArticle

  14. Published

    Cost-sensitive boosting algorithms: Do we really need them?

    Nikolaou, N., Edakunni, N., Kull, M., Flach, P. & Brown, G., 1 Sep 2016, In : Machine Learning. 104, 2, p. 359-384 26 p.

    Research output: Contribution to journalArticle

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