arXiv (All)
open access
How do I update my model? On the resilience of Predictive Process Monitoring models to change
Existing well investigated Predictive Process Monitoring techniques typically construct a predictive model based on past process executions, and then use it to predict the future of new ongoing cases, without the possibility of updating it with new cases when they complete their execution. This can
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- A Proactive Approach to Fault Tolerance Using Predictive Machine Learning Models in Distributed Systems#16664
- Predictive models for computing clusters: a case study based on Ilifu#416039
- On the Divergence of Accuracy and Mechanism Consistency in Time Series World Models#1157113
- Prognostic modelling#449335
- Stabilizing Performative Feedback Loops with Minimal Model Deployments#1083541
Record · ID 1014433
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive