Incremental Learning and Decremented Characterization of gene expression data analysis

In this study, we present Incremental Learning and
Decremented Characterization of Regularized Generalized
Eigenvalue Classification (ILDC-ReGEC), a novel algorithm
to train a generalized eigenvalue classifier with a substantially
smaller subset of points and features of the original
data. The proposed method provides a constructive way
to understand the influence of new training data on an existing
classification model and the grouping of features that
determine the class of samples. The proposed algorithm
is compared with other well known solutions. Experimental
results are conducted on publicly available datasets and
standard parameters are used for evaluation.