Pritam Anand

activity

20192024

most citedSupport Vector Regression via a Combined Reward Cum Penalty Loss Function

2 citations · 2 across the 6 of their papers we have counts for

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3 papers · 1 filter

cs.LG2019

A $ν$ - support vector quantile regression model with automatic accuracy control

Pritam Anand, Reshma Rastogi, Suresh Chandra

This paper proposes a novel ' $ν$ -support vector quantile regression' ( $ν$ -SVQR) model for the quantile estimation. It can facilitate the automatic control over accuracy by creating…

stat.ML2019

A new asymmetric $ε$ -insensitive pinball loss function based support vector quantile regression model

Pritam Anand, Reshma Rastogi, Suresh Chandra

In this paper, we propose a novel asymmetric $ε$ -insensitive pinball loss function for quantile estimation. There exists some pinball loss functions which attempt to incorporate th…

cs.LG2019★ 2 cited

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…

A ν- support vector quantile regression model with automatic accuracy control

A new asymmetric ε-insensitive pinball loss function based support vector quantile regression model

Support Vector Regression via a Combined Reward Cum Penalty Loss Function

A $ν$ - support vector quantile regression model with automatic accuracy control

A new asymmetric $ε$ -insensitive pinball loss function based support vector quantile regression model