Local Shrunk Discriminant Analysis (LSDA)

no code implementations • 3 May 2017 • Zan Gao, Guotai Zhang, Feiping Nie, Hua Zhang

Principal component analysis (PCA) is a traditional technique for unsupervised dimensionality reduction, which is often employed to seek a projection to best represent the data in a least-squares sense, but if the original data is nonlinear structure, the performance of PCA will quickly drop.

Supervised dimensionality reduction