NBLDA: Negative Binomial Linear Discriminant Analysis

We proposed a package for classification task which uses Negative Binomial distribution within Linear Discriminant Analysis (NBLDA). It is basically an extension of 'PoiClaClu' package to Negative Binomial distribution. The classification algorithms are based on the papers Dong et al. (2016, ISSN: 1471-2105) and Witten, DM (2011, ISSN: 1932-6157) for NBLDA and PLDA respectively. Although PLDA is a sparse algorithm and can be used for variable selection, the algorithm proposed by Dong et. al. is not sparse, hence, it uses all variables in the classifier. Here, we extent Dong et. al.'s algorithm to sparse case by shrinking overdispersion towards 0 (Yu et. al., 2013, ISSN: 1367-4803) and offset parameter towards 1 (as proposed by Witten DM, 2011). We support only the classification task with this version. However, the clustering task will be included with the following versions.

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