An Evaluation of Low Overhead Time Series Preprocessing Techniques for Downstream Machine Learning
An Evaluation of Low Overhead Time Series Preprocessing Techniques for Downstream Machine Learning
In this paper we address the application of pre-processing techniques to multi-channel time series data with varying lengths, which we refer to as the alignment problem, for downstream machine learning. The misalignment of multi-channel time series data may occur for a variety of reasons, such as missing data, varying sampling …