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Everything about Data-driven model

Class of computational model

Data-driven models are a class of computational models that primarily rely on historical data collected throughout a system's or process' lifetime to establish relationships between input, internal, and output variables. Commonly found in numerous articles and publications, data-driven models have evolved from earlier statistical models, overcoming limitations posed by strict assumptions about probability distributions. These models have gained prominence across various fields, particularly in the era of big data, artificial intelligence, and machine learning, where they offer valuable insights and predictions based on the available data. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Data-driven modelA 5-minute orientation
  2. Skim a recent paper: A maturity model enhancing data-driven circular manufacturingInfluential work since 2022
  3. Pick up a classic book: Model Driven ArchitectureThe most-reprinted book on the subject
  4. Read the landmark paper: A data-driven reflectance modelCited 594 times
  5. Go sideways: Soft computingA closely related topic
  6. Go sideways: Computational intelligenceA closely related topic

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🗂️ The subject at a glance

  1. Background
  2. Key Concepts

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics