A Comparative Analysis of Neural Network and Decision Tree Model for Detecting Result Anomalies

Optimization of indirect wastewater characterization: a hybrid approach based on decision trees, genetic algorithms and spectroscopy

“…First, their computational efficiency is notably superior to other techniques in terms of the present typology of study, such as neural networks and genetic algorithms. 42 This makes them an ideal choice for working with large datasets and for real-time applications. 43 Once the decision tree is trained, making predictions for new instances is fast because it involves traversing the tree from the root to a leaf node based on the feature values.…”