Author:
Baraybar-Huambo Juan,Gutiérrez-Cárdenas Juan
Publisher
Springer International Publishing
Reference29 articles.
1. Agrawal, A., Viktor, H.L., Paquet, E.: SCUT: multi-class imbalanced data classification using SMOTE and cluster-based undersampling. In: Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K), Lisbon, Portugal, vol. 1, pp. 226–234 (2015). https://doi.org/10.5220/0005595502260234
2. Aruna, S., Sudha, P.: An efficient identification of malnutrition with unsupervised classification using logical decision tree algorithm. Res. J. Pharm. Biol. Chem. Sci. 4(2), 365–373 (2016)
3. Azarkhish, I., Raoufy, M.R., Gharibzadeh, S.: Artificial intelligence models for predicting iron deficiency anemia and iron serum level based on accessible laboratory data. J. Med. Syst. 36(3), 2057–2061 (2012). https://doi.org/10.1007/s10916-011-9668-3
4. Batista, G., Prati, R., Monard, C.: A study of the behavior of several methods for balancing machine learning training data. ACM SIGKDD Explor. Newsl. 6(1), 20–29 (2004)
5. Bullón, C., Astete, R.: Determinantes de la Desnutrición Crónica de los Menores de Tres Años en las Regiones del Perú: Sub-Análisis de la Encuesta Endes 2000. Anales Científicos 77(2), 249 (2016). https://doi.org/10.21704/ac.v77i2.636