| KnowledgeMiner (yX) for Excel - Overview
|
There are three different editions of KnowledgeMiner (yX) for Excel plus a time unlimited Free version
for evaluation purposes: The entry level Copper edition (available in the
App Store, only),
the Silver edition for solving smaller and simpler modeling problems, and our Gold edition for
high-performance, high-end professional knowledge mining needs.
Table 1: Key parameters of all versions.
Excel
versions
|
Self-organized Analytical Model
|
Similar pattern
search
|
Diagram
generation
in Excel
|
Yearly
fees
|
eBook
|
2011
2008
2004
|
Forecasting, Modeling, Classification
|
Forecasting
|
Line, Prediction Interval, Scatter
|
No
|
Free
|
|
Table 2: Different key parameters.
|
Versions
|
Full support
of multiple
cores/CPUs
|
# of potential
inputs
supported
|
# of samples
supported
|
Model export
to Excel
|
Unrestricted
modeling/
forecasting
|
Price
|
|
Free
|
No
|
15
|
2,000
|
Yes
|
No/No
|
Free
|
|
Copper
|
Yes
|
25
|
5,000
|
Yes
|
Yes/Yes
|
App Store
|
|
Silver
|
Yes
|
250
|
50,000
|
Yes
|
Yes/Yes
|
Show
|
|
Gold
|
Yes
|
350
|
Excel sheet
|
Yes
|
Yes/Yes
|
Show
|
|
Table 3: Common modeling technologies and their applicability
to different data set dimensions.
|
Sample Size n
|
Small
number of inputs m
(m < 50)
|
Medium
number of inputs m
(49 < m < 500)
|
Large
number of inputs m
(499 < m < 50K)
|
Very Small
(n < 30)
|
yX, [R]
|
yX
|
yX
|
Small
(29 < n < 200)
|
yX, [R, NN]
|
yX, [R]
|
yX
|
Medium
(199 < n < 10K)
|
yX, R, NN
|
yX, [R, NN]
|
yX
|
Large
(10K < n < 1M)
|
yX, R, NN
|
yX, [R, NN]
|
yX
|
|
• NN - Neural Networks and other Machine Learning methods.
• R - Statistical regression methods.
• yX - Self-organizing, high-dimensional modeling in
KnowledgeMiner (yX) for Excel according to version, Copper, Silver, Gold, or on request.
• [.] - Can be applied under certain conditions only.
|
- Brings High-Performance Personal Knowledge Mining to Excel users with unprecedented
ease of model building and ease of model deployment likewise.
- Hides the complex processes of knowledge extraction, model development, dimension reduction,
variables selection, noise filtering to avoid overfitted models, and model validation to the user.
- Uses the familiar interface and functionality of Microsoft Excel for storing and organizing the data,
building models, and working with the generated models.
- Self-organizes linear or nonlinear, static or dynamic regression models
along with a equation that describes the data from up to 50,000 input variables.
- High-dimensional modeling by implementing unique model validation methods
which significantly help answering one key question
if the generated model reflects a causal relationship and to which extent
or if it just models noise. This leads to the concept of Descriptive Power of a model.
- Generated analytical models can be used for Status-Quo or What-If prediction,
analysis, simulation, or optimization problems in Excel.
- Nonparametric forecasting models for fuzzy objects
based on Similar Patterns technology.
- Free PDF copy of the book by Mueller/Lemke "Self-Organising
Data Mining."
| How KnowledgeMiner (yX) is Different |
Starting from the basic ideas in cybernetics to
the important influential works of A. G. Ivakhnenko in self-organizing modeling,
KnowledgeMiner (yX) for Excel is based on a proven 50-year history and development
of essential concepts in mathematics, statistics, information and computer science,
and systems theory. It implements 64-bit multithreaded, self-organizing modeling
algorithms to make efficient use of multi-core hardware and to significantly reduce
time-to-deploy of models by the factor of 10 or more compared to other data mining tools.
KnowledgeMiner (yX) was designed to generate models objectively
by taking as much as possible work and subjective decisions from
the user to enable true knowledge extraction from noisy data, which
must only be minimally influenced by any expectations or assumptions
of the user respectively modeler. A consequence of this strict approach is simplicity and
consistent ease of use of the tool.
KnowledgeMiner (yX) for Excel is forecasting software, where you
can analyze and forecast processes that take place over time,
statistical analysis and modeling software to better understand
how a complex problem can be described
mathematically, and classification software in one tool.
It provides a fast and unique way for scientists and business users
to generate and apply reliable models from low- to high-dimensional
noisy data for a wide range of problems.
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