home
***
CD-ROM
|
disk
|
FTP
|
other
***
search
/
MacWorld 1999 June
/
Macworld (1999-06).dmg
/
Shareware World
/
Education
/
KnowledgeMiner 3.0
/
Info
/
Version History
< prev
Wrap
Text File
|
1999-03-22
|
3KB
|
72 lines
KnowledgeMiner History
March/23/1999 - version 3.0
• New modeling method: Self-organizing Fuzzy Rule Induction (Fuzzy-GMDH)
• available for the first time on any personal computer
• combines modeling of fuzzy objects with natural language-like interpretational power of the generated models
• larger and now customizable data sheet (up to 10,000 rows/ 200 columns)
• improved GMDH by information matrix optimization
• improved and updated Help menu (AppleGuide, Balloons)
• updated and extended examples collection
• fixed bug that may occur when reading ASCII text files
• scaled into Copper, Silver and Gold editions
June/28/1998 - version 2.2.3
• first PPC only version
• improved Analog Complexing method
• several bugs are fixed making the program more stable under low memory conditions
• redesigned "Modeling" and "Window" menus
February/4/1998 - version 2.2.2
• fixed bug that may occur when reading large files
• new features will not be supported for the 68k based version beginning from this version
December/15/1997 - version 2.2.1
• 32k ASCII text import limit removed
• fixed bug that causes a crash when calculating a large number of formulas in spreadsheet
• fixed bug on PowerMac that does a wrong cell assignment when verifying a spreadsheet input by mouse click
• improved and updated the text files and apple guide
October/24/1997 - version 2.1
• tutorial updated - new context check features
• removed bug that allowed opening two documents at once on PowerMac
October/1/1997 - version 2.0
• optimized for PPC and 68kFPU based Macs
• PPC native app runs 8-10 times faster than 68k based version. Now it is possible to mine very large data sets for
relevant relations or patterns within minutes instead of days.
• Analog Complexing
• available for the first time on a personal computer (Mac) as shareware.
• shows automatically a prediction interval graphically (the calculated possible upper and lower limits) along with
the most likely prediction of points. Now a prediction consists not only of sharp points but reflects also the
inherent fuzziness and uncertainty of the objects. Applied to financial time series forecasting, e.g., this view
focuses on the demand to consider the volatility of assets to get more reliable forecasts and decisions.
• optimized modeling algorithms to make self-organization of structures and knowledge extraction from data far
more effective than neural networks or statistics
• Lite version
• now has a larger table to work with data
• two levels to setup modeling
• a standard and
• an advanced modeling setup dialog
May/1/1997 - initial release