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Benchmarking changepoint detection algorithms on cardiac time series
This work represents the first time change point detection algorithms have been compared in a meaningful way and utilized in a classification task, which demonstrates the effect of changepoint algorithm choice on application performance.
Addressing Class Imbalance in Classification Problems of Noisy Signals by using Fourier Transform Surrogates
To quantify how well the distributions of the surrogates and the original data match, we evaluated a trained classifier on surrogates of correctly classified examples, and summarized these conditional predictions in a confusion matrix.
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