# Incremental Sparse Bayesian Ordinal Regression

@article{Li2018IncrementalSB, title={Incremental Sparse Bayesian Ordinal Regression}, author={Chang Li and M. de Rijke}, journal={Neural networks : the official journal of the International Neural Network Society}, year={2018}, volume={106}, pages={ 294-302 } }

Ordinal Regression (OR) aims to model the ordering information between different data categories, which is a crucial topic in multi-label learning. An important class of approaches to OR models the problem as a linear combination of basis functions that map features to a high-dimensional non-linear space. However, most of the basis function-based algorithms are time consuming. We propose an incremental sparse Bayesian approach to OR tasks and introduce an algorithm to sequentially learn the… Expand

#### 6 Citations

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