Your browser doesn't support javascript.
loading
A Preliminary Study on the Effectiveness of K-Nearest Neighbor Algorithm Based on Local Mean for Classification of Bioinformatics Data.
Yi, Jingrui; Rao, Qiang; Zhang, Qi; Zhang, Junbao; Song, Liya; Wu, Hao.
Afiliación
  • Yi J; College of Pharmaceutical and Biological Engineering, Shenyang University of Chemical Technology, Shengyang 110142, China.
  • Rao Q; College of Pharmaceutical and Biological Engineering, Shenyang University of Chemical Technology, Shengyang 110142, China.
  • Zhang Q; College of Computer Science and Technology, Shenyang University of Chemical Technology, Shengyang 110142, China.
  • Zhang J; College of Pharmaceutical and Biological Engineering, Shenyang University of Chemical Technology, Shengyang 110142, China.
  • Song L; College of Pharmaceutical and Biological Engineering, Shenyang University of Chemical Technology, Shengyang 110142, China.
  • Wu H; College of Pharmaceutical and Biological Engineering, Shenyang University of Chemical Technology, Shengyang 110142, China.
Stud Health Technol Inform ; 308: 410-416, 2023 Nov 23.
Article en En | MEDLINE | ID: mdl-38007767
The preliminary classification of biological class data is of great importance for bioinformatics. One can quickly classify object data by comparing their existing features with known traits. k-nearest neighbor algorithm is easy to apply in this field, but its drawbacks make it less meaningful to improve the efficiency of the algorithm by simply changing the distance model, so this study uses a local mean-based k-nearest neighbor classifier and compares the accuracy of the predicted classification of six different distance models used. The prediction accuracies in the experimental results were all greater than 70%, and the highest accuracy was achieved in different data sets for all distance models with K=2; the prediction accuracy of Minkowski distance with different parameters had the highest volatility in the test.and the experimental results can be used as a reference for related practitioners.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Biología Computacional Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Biología Computacional Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos