1 min to read
Block Model Guided Unsupervised Feature Selection
How to effectively select features by utilizing SBM.
Video
The area of feature selection is a critical initial step in data mining and vital for its success. It has been extensively studied[21] with a recent innovation of graph driven feature selection where a featured dataset 𝑌, adjacency matrix 𝐴.
A challenge in these domains is that the nodal attributes can be a noisy/irrelevant or even redundant high dimensional feature space. This can yield suboptimal solutions if we assume all the features associated with the nodes and the graph structure are complementary [33,46].
This paper takes the novel approach of first building a block model on the graph and then using the block model for feature selection.
Comments