Modelling and statistical learning

We use intelligent modelling and statistical learning to build mathematical, statistical and logic models between output and input variables.

Intelligent modelling and statistical learning aiming to build mathematical, statistical and logic models between output variables (features or attributes) and input variables for a particular problem.

This could include multiple aspects:

• symbolic regression and mathematical modelling
• classification: class imbalance, missing data
• unsupervised learning or clustering
• categorical and ordinal data analysis.

Real-world applications

Modelling and statistical learning has been important for solving problems in real-world applications in areas such as:

• primary industry
• climate change
• biomedical, medical, and health tasks.