Time Series Ssa

Training Algorithm Details

This class implements the general anomaly detection transform based on Singular Spectrum Analysis (SSA). SSA is a powerful framework for decomposing the time-series into trend, seasonality and noise components as well as forecasting the future values of the time-series. In principle, SSA performs spectral analysis on the input time-series where each component in the spectrum corresponds to a trend, seasonal or noise component in the time-series. For details of the Singular Spectrum Analysis (SSA), refer to this document.