This repository contains the code to run the experiments and generate the conference paper "Implicitly Constrained Least Squares Classification" and the extended version of this work "Robust Semi-supervised Least Squares Classification by Implicit Constraints" by Jesse H. Krijthe and Marco Loog:
Krijthe, J. H., & Loog, M. (2017). Robust Semi-supervised Least Squares Classification by Implicit Constraints. Pattern Recognition, 63, 115–126. https://doi.org/10.1016/j.patcog.2016.09.009
Krijthe, J. H., & Loog, M. (2015). Implicitly Constrained Semi-Supervised Least Squares Classification. In E. Fromont, T. De Bie, & M. van Leeuwen (Eds.), Advances in Intelligent Data Analysis XIV. Lecture Notes in Computer Science, vol 9385. (pp. 158–169). Saint Étienne. France: Springer. https://doi.org/10.1007/978-3-319-24465-5_14
The actual code for the methods involved has been placed in a separate R package (RSSL). Version 8814741a2870d4a1b06eef1fdf97e1342410eec3 of this package contains the code used to run the experiments in the paper.
make latex pdfcrop R (3.0.0) with packages RSSL (commit: 8814741a2870d4a1b06eef1fdf97e1342410eec3), install using install_github("jkrijthe/RSSL",ref="8814741a2870d4a1b06eef1fdf97e1342410eec3") from the devtools package createdatasets ggplot2
The experiments were originally run under Mac OS X 10.10.
This publication was supported by the Dutch national program COMMIT, project P23.