Outlier detection and least trimmed squares approximation using semi-definite programming
Computational Statistics & Data Analysis
Support Vector Machines with the Ramp Loss and the Hard Margin Loss
Operations Research
A DIAMOND method of inducing classification rules for biological data
Computers in Biology and Medicine
A DIAMOND method for classifying biological data
ICMB'10 Proceedings of the Second international conference on Medical Biometrics
Review: Supervised classification and mathematical optimization
Computers and Operations Research
Column Generation for the Minimum Hyperplanes Clustering Problem
INFORMS Journal on Computing
| Hi-index | 0.00 |
Motivated by the significant advances in integer optimization in the past decade, we introduce mixed-integer optimization methods to the classical statistical problems of classification and regression and construct a software package called CRIO (classification and regression via integer optimization). CRIO separates data points into different polyhedral regions. In classification each region is assigned a class, while in regression each region has its own distinct regression coefficients. Computational experimentations with generated and real data sets show that CRIO is comparable to and often outperforms the current leading methods in classification and regression. We hope that these results illustrate the potential for significant impact of integer optimization methods on computational statistics and data mining.