Search Results for author: Pritam Anand

Found 5 papers, 1 papers with code

Improvement over Pinball Loss Support Vector Machine

1 code implementation2 Jun 2021 Pritam Anand, Reshma Rastogi, Suresh Chandra

The existing Pin-SVM model requires to solve the same optimization problem for all values of $\tau$ in $[ -1, 1]$.

Binary Classification valid

Learning a powerful SVM using piece-wise linear loss functions

no code implementations9 Feb 2021 Pritam Anand

In this paper, we have considered general k-piece-wise linear convex loss functions in SVM model for measuring the empirical risk.

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

no code implementations21 Oct 2019 Pritam Anand, Reshma Rastogi, Suresh Chandra

The proposed $\nu$-SVQR model uses the $\nu$ fraction of training data points for the estimation of the quantiles.

regression

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

no code implementations19 Aug 2019 Pritam Anand, Reshma Rastogi, Suresh Chandra

In this paper, we propose a novel asymmetric $\epsilon$-insensitive pinball loss function for quantile estimation.

regression

Support Vector Regression via a Combined Reward Cum Penalty Loss Function

no code implementations28 Apr 2019 Pritam Anand, Reshma Rastogi, Suresh Chandra

In this paper, we introduce a novel combined reward cum penalty loss function to handle the regression problem.

regression

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