About
A branch of predictive analysis that attempts to predict some future state of a business process.
Benchmarks
Greatest papers with code
Predictive Business Process Monitoring with LSTM Neural Networks
First, we show that LSTMs outperform existing techniques to predict the next event of a running case and its timestamp.
MULTIVARIATE TIME SERIES FORECASTING PREDICTIVE PROCESS MONITORING TIME SERIES PREDICTION
Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction
• farbodtaymouri/GanPredictiveMonitoring
• 
Predictive process monitoring aims to predict future characteristics of an ongoing process case, such as case outcome or remaining timestamp.
Outcome-Oriented Predictive Process Monitoring: Review and Benchmark
Predictive business process monitoring refers to the act of making predictions about the future state of ongoing cases of a business process, based on their incomplete execution traces and logs of historical (completed) traces.
Fire Now, Fire Later: Alarm-Based Systems for Prescriptive Process Monitoring
Predictive process monitoring is a family of techniques to analyze events produced during the execution of a business process in order to predict the future state or the final outcome of running process instances.
Temporal Stability in Predictive Process Monitoring
• irhete/stability-predictive-monitoring
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We then show that temporal stability can be enhanced by hyperparameter-optimizing random forests and XGBoost classifiers with respect to inter-run stability.
Explainable Predictive Process Monitoring
• PyRicky/LSTM_Generic_explainable
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Predictive Business Process Monitoring is becoming an essential aid for organizations, providing online operational support of their processes.
Alarm-Based Prescriptive Process Monitoring
Predictive process monitoring is concerned with the analysis of events produced during the execution of a process in order to predict the future state of ongoing cases thereof.
Evaluating Explainable Methods for Predictive Process Analytics: A Functionally-Grounded Approach
Current explainable machine learning methods, such as LIME and SHAP, can be used to interpret black box models.