Abstract
Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.
X. Blanco Valencia—This work is supported by Faculty of Engineering from University of Salamanca.
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Blanco Valencia, X., Bastidas Torres, D., Piñeros Rodriguez, C., Peluffo-Ordóñez, D.H., Becerra, M.A., Castro-Ospina, A.E. (2018). Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10813. Springer, Cham. https://doi.org/10.1007/978-3-319-78723-7_3
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