A novel kNN algorithm with data-driven k parameter computation

作者：Zhang, Shichao; Cheng, Debo^*; Deng, Zhenyun; Zong, Ming; Deng, Xuelian

来源：Pattern Recognition Letters, 2018, 109: 44-54.

DOI：10.1016/j.patrec.2017.09.036

• kNN method
• kNN prediction
• Parameter computation

This paper studies an example-driven k-parameter computation that identifies different k values for different test samples in kNN prediction applications, such as classification, regression and missing data imputation. This is carried out with reconstructing a sparse coefficient matrix between test samples and training data. In the reconstruction process, an l(1)-norm regularization is employed to generate an element-wise sparsity coefficient matrix, and an LPP (Locality Preserving Projection) regularization is adopted to keep the local structures of data for achieving the efficiency. Further, with the learnt k value, k NN approach is applied to classification, regression and missing data imputation. We experimentally evaluate the proposed approach with 20 real datasets, and show that our algorithm is much better than previous k NN algorithms in terms of data mining tasks, such as classification, regression and missing value imputation.

• 出版日期2018-7-15
• 单位广西中医药大学; 广西师范大学