Conditional Linear Regression

Previous work in machine learning and statistics commonly focuses on building models that capture the vast majority of data, possibly ignoring a segment of the population as outliers. By contrast, we may be interested in finding a segment of the population for which we can find a linear rule capable of achieving more accurate predictions. We give an efficient algorithm for the conditional linear regression task, which is the joint task of identifying a significant segment of the population, described by a k-DNF, along with its linear regression fit.

Authors

• Diego Calderon
• Brendan Juba Washington University in St Louis, USA
• Zongyi Li Huazhong University of Science and Technology
• Lisa Ruan

Keywords

No keywords are indexed for this paper.