Optimized Early Prediction of Business Processes with Hyperdimensional Computing
Fatemeh Asgarinejad,
Anthony Thomas,
Ryan Hildebrant
et al.
Abstract:There is a growing interest in the early prediction of outcomes in ongoing business processes. Predictive process monitoring distills knowledge from the sequence of event data generated and stored during the execution of processes and trains models on this knowledge to predict outcomes of ongoing processes. However, most state-of-the-art methods require the training of complex and inefficient machine learning models and hyper-parameter optimization as well as numerous input data to achieve high performance. In… Show more
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