1 code implementation • 11 Nov 2021 • Rajiv Sambasivan, Mark Burgess, Jörg Schad, Arthur Keen, Christopher Woodward, Alexander Geenen, Sachin Sharma
This graph is refined by applying sparsity-based statistical learning methods.
1 code implementation • 9 Nov 2018 • Rajiv Sambasivan, Sourish Das, Sujit K Sahu
Statistical Machine Learning (SML) refers to a body of algorithms and methods by which computers are allowed to discover important features of input data sets which are often very large in size.
no code implementations • 26 Oct 2017 • Rajiv Sambasivan, Sourish Das
The second step of the algorithm consists of using a suitable classifier to determine the class labels for the non-homogeneous leaf nodes.
no code implementations • 24 Jul 2017 • Rajiv Sambasivan, Sourish Das
In the experiments reported in this study, we found that the predictive performance of the proposed approach matched the predictive performance of Gradient Boosted Trees.
no code implementations • 4 Mar 2017 • Rajiv Sambasivan, Sourish Das
A Gaussian Process is used to model the yield curve.
no code implementations • 17 Aug 2016 • Rajiv Sambasivan, Sourish Das
Datasets with a mixture of numerical and categorical attributes are routinely encountered in many application domains.
no code implementations • 17 Sep 2015 • Sourish Das, Sasanka Roy, Rajiv Sambasivan
A known limitation in the application of Gaussian Processes to regression tasks is that the computation of the solution requires performing a matrix inversion.