Forecasting of Univariate Time Series Using the Pattern
Sequence-Based Forecasting (PSF) Algorithm
Description
Pattern Sequence Based Forecasting (PSF) takes univariate
time series data as input and assist to forecast its future values.
This algorithm forecasts the behavior of time series
based on similarity of pattern sequences. Initially, clustering is done with the
labeling of samples from database. The labels associated with samples are then
used for forecasting the future behaviour of time series data. The further
technical details and references regarding PSF are discussed in Vignette.