Deducing Optimal Classification Algorithm for Heterogeneous Fabric
This work provides guidance for researchers in materials science or geology on algorithm selection, but it is incremental as it applies existing methods to a new dataset.
The authors tackled the problem of selecting the optimal machine learning algorithm for heterogeneous fabric classification by testing five algorithms on a synthetic dataset, identifying Random Forest as the most appropriate.
For defining the optimal machine learning algorithm, the decision was not easy for which we shall choose. To help future researchers, we describe in this paper the optimal among the best of the algorithms. We built a synthetic data set and performed the supervised machine learning runs for five different algorithms. For heterogeneous rock fabric, we identified Random Forest, among others, to be the appropriate algorithm.