April 25, 2007 — Script Software (scriptsoftware.com) announced
today version 5.3.3 of KnowledgeMiner.
KnowledgeMiner can be downloaded from:
http://www.knowledgeminer.com/
– [new] improved significance testing during model self-organization
to avoid using non-relevant inputs in a model;
– [new] call for papers for the 2nd International Workshop on
Inductive Modeling which aims at state, progress, applications, and
outlook of inductive modeling technologies like self-organizing
networks of active neurons: http://www.iwim2007.org/
– [bug] when building models from just 2 inputs fixed (in version X
5.3.2, only);
– [bug] fixed that may produce, for very complex nonlinear models,
minor differences between the generated model equation and the
calculated model output (graphics); the export of models to MS Excel
has not been affected by this bug;
– [bug] fixed that occasionally causes KM to crash when reading the
clipboard at program startup;
KnowledgeMiner is being used by NASA, Boeing, MIT, Columbia, Notre
Dame, University of Hamburg, Mobil Oil, Pfizer Inc., Dean & Company,
Demetra and many other corporations, universities, research
institutions, projects and individuals around the world. Because it
is a knowledge discovery (structure) via data mining (information) it
can be used in any field of human inquiry to reveal new and
previously unknown relationships in data.
The software application KnowledgeMiner employs a set of unique
inductive learning and self-organizing modeling technologies: GMDH
Neural Networks, Fuzzy Rule Induction, and Analog Complexing pattern
recognition for time series prediction, classification, modeling,
clustering, and diagnosis of complex ill-defined systems.
Multileveled self-organization and validation approaches make it not
only possible to generate reliable individual and hybrid models in a
most objective way, but they also provide an explanation component on
the fly in form of algebraic or difference equations, fuzzy rules, or
a set of similar patterns. This extracted knowledge can be directly
used to improve model results, to get new insights into the system,
and to aid decisions.
KnowledgeMiner is most often purchased and used for stocks,
currencies, and financial trading. But KnowledgeMiner is useful in
every field of research and has been used with great success in
recent projects in cancer research, prediction of wastewater
pre-precipitation and wastewater reuse, to identify walking gait
abnormalities for persons wearing prosthetic legs, analyzing medical
data obtained from observing eye movement of children both healthy
and children that display reading abnormalities, modeling and
prediction of regional economies and related economic problems,
prediction of environmental activity of toxicity residues of chemical
compounds (especially pesticides) from the compounds’ chemical
structure, problematic pharmaceutical manufacturing processes,
researching various aspects of language teaching and learning,
modeling China’s macro economy for the government, and discovering
the relationship between altered MR intensities in the caudate
nucleus and patient disability in multiple sclerosis, etc. All of
which shows the broad range of applications that KnowledgeMiner can
be harnessed for to apply to a variety research.
KnowledgeMiner contains many pre-modeled examples from various
application areas, several sample scripts for program-to-program
communication, a sample KDD workflow applescript, TransformModel,
Business Intelligence Workflow Case Study, and includes a PDF copy of
the book called “Self-Organising Data Mining. Extracting Knowledge
From Data.” by Prof. J.-A. Mueller and Frank Lemke. This book is the
easiest way to learn about data mining, self-organizing modeling and
the basic ideas behind KnowledgeMiner.
KnowledgeMiner comes in a student version all the way up to a
Platinum edition that comes with 5 hours consulting time with Frank
Lemke one of the world’s leading experts in data mining technology.
KnowledgeMiner software is easy to use but now a consultant is
available to help anyone get started with their simple or more
complex datasets. Never before has there been a knowledge discovery
via data mining package that combined this level of power, ease of
use, and support by an expert. KnowledgeMiner is the first knowledge
discovery via data mining software package for the individual.
Users Rave
“I must say old timers in modeling are dumbfounded by the power of
your program.” Charles Koehler, Ph.D.
“KnowledgeMiner is the only product that I have found that makes it
easy to try non-standard equation formats on a data set. Many
standard regression tools are as easy, but they limit you to a small
set of potential relationships. KnowledgeMiner combines
spreadsheet-like set up with an algorithm that doesn’t “over fit” the
model. Also, the output is in a readily usable format (e.g. not C++
code).” Ware Adams, Dean & Company, a strategy consulting firm in the
U.S.
“The Alpine skiing and Athletic French Federation have contacted my
laboratory to build a profile of their elite athletes. In this case,
KnowledgeMiner helped me save a lot of time and gave me models on the
most important variables, and pointed out the less relevant.” Fabrice
Viale, Doctoral thesis student Laboratoire de Physiologie, Faculte de
Medecine, France
“KnowledgeMiner is the most advanced implementation of the GMDH
approach today. It uses the inductive method, which is different from
deductive techniques used commonly for modeling on principle.
Recently many important results were demonstrated using this software
tool. They show its advantages over other well-known software.” Prof.
Alexey G. Ivakhnenko, author of the GMDH approach.
“I like KnowledgeMiner because its algorithm does not make any
assumtions on the underlying data; well, at least not during the
initial model-building phase. I also like the fact that it generates
sets of equations that the user can review with detailed
understanding of the interactions and dependencies of each variable.
Also, the algorithm(s) behave surprising well under extreme
conditions for certain complex dynamical systems. Congratulations for
your excellent work.” Alexis Pobedonostzeff, Pfizer Inc.
Director, Health Care Issues Analysis & Management
“I’m a physicist by training, working as a radar engineer on some
cutting edge target recognition/classification technologies. I am now
using KM to circumvent all the past pattern recognition algorithms
which have been years (and millions of $) in development by the armed
forces. Although I am just now starting to use KM in this
application, my initial indications are that KM is providing a more
robust,complete and more accurate classification capability than any
of the previously used algorithms, and with comparatively no effort
on my part” Herb, Vista Technologies, Inc.
SUMMARY
KnowledgeMiner is the leading package on Mac OS X that combines data
mining with leading edge algorithms to do prediction. It is based on
decades of work in different countries by top researchers. Using
KnowledgeMiner can save researchers months of work and can help in
finding structure in information or knowledge in data.
ABOUT SCRIPT SOFTWARE
Script Software has been making essential software for the Macintosh
and Windows since 1987. They are the creators of the award winning
CopyPaste, iClock, iKey, iWatermark, KnowledgeMiner, iBeenFramed,
Project Timer Pro, ID Tunes, iSay, Easy Card, iStar Karaoke, iStar
Composer and ChatFX
For more information on KnowledgeMiner or a review copy or to
interview Frank Lemke or Julian Miller for a podcast please contact
us.