Codeless Time Series Analysis with KNIME

Chapter 8: Audio Signal Classification with an FFT and a Gradient-Boosted Forest

In this chapter, we will break from forecasting to perform a different type of machine learning on time series data: classification. Using the Fourier transform, we will transform our data and perform dimensionality reduction, then train a familiar classification model with input and target columns to classify an audio source.

The Fourier transform, however, has a myriad of applications in time series analysis beyond classification. It is used to better explore time series data in search of patterns by shifting to the frequency domain where we can view component seasonal patterns. Furthermore, it is used to construct complex state space models capable of incorporating ...