TY - JOUR
T1 - Dynamic nearest neighbor
T2 - An improved machine learning classifier and its application in finances
AU - Camacho-Urriolagoitia, Oscar
AU - López-Yáñez, Itzamá
AU - Villuendas-Rey, Yenny
AU - Camacho-Nieto, Oscar
AU - Yáñez-Márquez, Cornelio
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/10/1
Y1 - 2021/10/1
N2 - The presence of machine learning, data mining and related disciplines is increasingly ev-ident in everyday environments. The support for the applications of learning techniques in topics related to economic risk assessment, among other financial topics of interest, is relevant for us as human beings. The content of this paper consists of a proposal of a new supervised learning algorithm and its application in real world datasets related to finance, called D1-NN (Dynamic 1-Nearest Neighbor). The D1-NN performance is competitive against the main state of the art algorithms in solving finance-related problems. The effectiveness of the new D1-NN classifier was compared against five supervised classifiers of the most important approaches (Bayes, nearest neighbors, support vector machines, classifier ensembles, and neural networks), with superior results overall.
AB - The presence of machine learning, data mining and related disciplines is increasingly ev-ident in everyday environments. The support for the applications of learning techniques in topics related to economic risk assessment, among other financial topics of interest, is relevant for us as human beings. The content of this paper consists of a proposal of a new supervised learning algorithm and its application in real world datasets related to finance, called D1-NN (Dynamic 1-Nearest Neighbor). The D1-NN performance is competitive against the main state of the art algorithms in solving finance-related problems. The effectiveness of the new D1-NN classifier was compared against five supervised classifiers of the most important approaches (Bayes, nearest neighbors, support vector machines, classifier ensembles, and neural networks), with superior results overall.
KW - Finance risk prediction
KW - Machine learning
KW - Supervised classification
UR - http://www.scopus.com/inward/record.url?scp=85115771755&partnerID=8YFLogxK
U2 - 10.3390/app11198884
DO - 10.3390/app11198884
M3 - Artículo
AN - SCOPUS:85115771755
SN - 2076-3417
VL - 11
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 19
M1 - 8884
ER -