Interactive Model Selection Guide

Find the suitable machine learning approach for your resin formulation task. Adjust the parameters to your project situation to receive an informed recommendation.

1. Define Your Scenario

Available Data Size: 150 Samples

LowModerateHigh

Task Type

Explicit Knowledge (Ontology) Available?

Interpretability Required?

2. Your Tailored Recommendation

Details on Model Categories

Source Document: ML Models for Resin Optimization

Note: The embedded PDF document is in German.

Interactive Model Selection Guide

Classic ML Methods (Random Forest, SVM, etc.)

Probabilistic & Bayesian Methods (GPR)

Deep Neural Networks (Deep Learning, GNNs)

Symbolic & Knowledge-Based Approaches