1 research outputs found
Support Vector Regression via a Combined Reward Cum Penalty Loss Function
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 data points which lie outside the -tube of the
regressor and also assigns reward for the data points which lie inside of the
-tube of the regressor. The combined reward cum penalty loss function
based regression (RP--SVR) model has several interesting properties
which are investigated in this paper and are also supported with the
experimental results.Comment: For any assistance , reader can contact on email with Pritam Anand.
Email id - [email protected]. The valuable opinion/comments on the work
are welcomed. Looking for collaboration especially for speeding up the
solution of optimization problem