What is Data Dimensionality Reduction

Data dimensionality reduction is the transformation of high-dimensional data into a meaningful representation of reduced dimensionality. The goal is to find the important relationships between parameters and reproduce those relationships in a lower dimensionality space. Ideally, the obtained representation has a dimensionality that corresponds to the intrinsic dimensionality of the data. Dimensionality reduction is important in many domains, since it facilitates classification, visualization, and compression of high-dimensional data. In our work it’s performed using Curvilinear Distance Analysis