Posts tagged machine-learning
Principal Component Analysis
- 14 May 2021
The Principal Component Analysis (PCA) is a dimension reduction technique widely used. Given a dataset with \(n\) features, the aim is to have \(k\) feature with \(k\le n\) so as the features retain most of the variation present in all of the original variables.
Empirical Mode Decomposition
- 06 May 2021
Introduced by Hilbert–Huang, Empirical Mode Decomposition (EMD) is a data-driven method that used as a propelling tool for analyzing and decomposing non-stationary and non-linear data. EMD generates a finite and often small number of the frequency and amplitude modulated signals, intrinsic mode functions (IMF).