A classification tree is grown by repeated partitioning of the dataset based on a predefined split criterion. The node split in the growth process depends only on the class ratio of the data chunk that gets split in …
When data science solutions are deployed in practice, seldom do the conditions on the ground match the theoretical assumptions of the algorithms. In this project, we look at algorithms and approaches that can operate …
We propose a Semi-Supervised Learning (SSL) methodology that explicitly encodes different necessary priors to learn efficient representations for nodes in a network. The key to our framework is a semi-supervised cluster …
