|A.G. Ivakhnenko, is the author of the unparalleled self-organizing, noise immune, inductive modeling and knowledge mining technology known as GMDH. A major difficulty in modeling complex systems in such unstructured areas as economics, ecology, sociology, and others is the problem of the researcher introducing his or her own prejudices into the model. Since the system in question may be extremely complex, the basic assumptions of the modeler may be vague guesses at best. It is not surprising that many of the results in these areas are vague, ambiguous, and extremely qualitative in nature.|
|Obtaining a model from data is easy. Obtaining a model from data that reliably reflects the underlying relationship in the data with some certainty is hard work. This is especially true for noisy data. Noisy data are everywhere so you most probably will use them. To systematically avoid overfitting - that is, when the model fits to random cases (noise) and therefore can only have poor predictive power, which makes it useless -, to get optimized transfer functions in Active Neurons, and to self-organize robust optimal complex models with optimal predictive power, Insights employs original concepts of model validation at different levels of the self-organizing modeling process. Together with our Live Prediction Validation, application of data mining models is now more reliable, stable, and valuable than ever before.|
|Insights is the new brand of our former KnowledgeMiner product.
© 2001-2014 KnowledgeMiner Software