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KnowledgeMiner 4.0 - Powerful Data-Mining Made Easy (knowledge-miner-40.hqx)

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From: julian miller
Subject: KnowledgeMiner 4.0 - Powerful Data-Mining Made Easy

Revolutionary learning and modeling tool that goes beyond neural nets by
using gmdh and analog complexing. It has the power to predict with an ease
and accuracy that is not available in any other software on any other
platform. Now Applescriptable.

What is KnowledgeMiner?
KnowledgeMiner is a data mining tool that enables anyone to use its unique
form of modeling to quickly visualize new possibilities. It is an artificial
intelligence tool designed to easily extract hidden knowledge from data. It
was built on the cybernetic principles of self-organization: Learning a
completely unknown relationship between output and input of any given system
in an evolutionary way from a very simple organization to an optimally
complex one.

Why choose KnowlegeMiner?
The main advantages of the inductive KnowledgeMiner approach are:

* Only minimal, uncertain a priori information about the system is
required. That means, even if you have no experience in modeling, data
analysis or designing a neural network you will be able to model, analyze
and predict complex relationships of nearly any kind of system.

* A very fast and effective learning process for a personal computer.
That means you can solve problems on your desktop in a reasonable time which
you may have never thought possible.

* Modeling short and noisy data samples. That means, you can deal with a
problem as is and don't have to construct artificial conditions for your
modeling method to get it work.

* Output of an optimally complex model. Generally you can be sure to get
a model at the end of the automated modeling process which can be expected
not to be overfitted. Overfitted models are not able to predict inherent
relationships between variables.

* Output of an analytical model as a transparent explanation component.
That means, you can evaluate the analytical model to explain the obtained
results immediately after modeling.