3 papers
cs.LG2019
A - support vector quantile regression model with automatic accuracy control
Pritam Anand, Reshma Rastogi, Suresh Chandra
This paper proposes a novel '-support vector quantile regression' (-SVQR) model for the quantile estimation. It can facilitate the automatic control over accuracy by creating…
stat.ML2019
A new asymmetric -insensitive pinball loss function based support vector quantile regression model
Pritam Anand, Reshma Rastogi, Suresh Chandra
In this paper, we propose a novel asymmetric -insensitive pinball loss function for quantile estimation. There exists some pinball loss functions which attempt to incorporate th…
cs.LG2019
Support Vector Regression via a Combined Reward Cum Penalty Loss Function
Pritam Anand, Reshma Rastogi, Suresh Chandra
In this paper, we introduce a novel combined reward cum penalty loss function to handle the regression problem. The proposed combined reward cum penalty loss function penalizes the…