Neuton requires fewer training samples than traditional
neural networks or classical non-neural algorithms (xgboost, RF, etc.).
A Neuton-trained model is 10-100 times smaller than that
of other trained neural networks and traditional non-neural algorithms.
The resulting models are faster than those built by
Our benchmark results show that in the vast majority
of cases, Neuton achieves a higher level of accuracy than algorithms traditionally used for
regression and classification problems.
Neuton automatically resolves the issue of retraining
Neuton is designed and optimized to be utilized across
multiple user demographics, even those who do not have special skills in machine learning.