Kernel Corrector LSTM

arXiv:2404.18273v1 Announce Type: new
Abstract: Forecasting methods are affected by data quality issues in two ways: 1. they are hard to predict, and 2. they may affect the model negatively when it is updated with new data. The latter issue is usually addressed by pre-processing the data to remove those issues. An alternative approach has recently been proposed, Corrector LSTM (cLSTM), which is a Read \& Write Machine Learning (RW-ML) algorithm that changes the data while learning to improve its …

abstract alternative arxiv cs.lg data data quality data quality issues forecasting issue kernel lstm pre-processing processing quality type