the winmine toolkit max chickering. build statistical models from data dependency networks bayesian...
TRANSCRIPT
![Page 1: The WinMine Toolkit Max Chickering. Build Statistical Models From Data Dependency Networks Bayesian Networks Local Distributions –Trees Multinomial](https://reader035.vdocuments.net/reader035/viewer/2022081700/56649eba5503460f94bc2ab0/html5/thumbnails/1.jpg)
The WinMine Toolkit
Max Chickering
![Page 2: The WinMine Toolkit Max Chickering. Build Statistical Models From Data Dependency Networks Bayesian Networks Local Distributions –Trees Multinomial](https://reader035.vdocuments.net/reader035/viewer/2022081700/56649eba5503460f94bc2ab0/html5/thumbnails/2.jpg)
Build Statistical Models From Data
• Dependency Networks
• Bayesian Networks
• Local Distributions– Trees
• Multinomial / Binary Multinomial• Gaussian / Binary Gaussian• Log Gaussian / Binary Log Gaussian
– Complete Tables
![Page 3: The WinMine Toolkit Max Chickering. Build Statistical Models From Data Dependency Networks Bayesian Networks Local Distributions –Trees Multinomial](https://reader035.vdocuments.net/reader035/viewer/2022081700/56649eba5503460f94bc2ab0/html5/thumbnails/3.jpg)
Data Processing Tools
• DataConverter.exe (Interactive)Convert raw text or SQL data into XML format
• DataCheck.exe (Command-line)Extract basic statistics from data
• DataJoin.exe (Command-line)Perform a join between two datasets
• DataSplit.exe (Command-line)Split data into train/test
![Page 4: The WinMine Toolkit Max Chickering. Build Statistical Models From Data Dependency Networks Bayesian Networks Local Distributions –Trees Multinomial](https://reader035.vdocuments.net/reader035/viewer/2022081700/56649eba5503460f94bc2ab0/html5/thumbnails/4.jpg)
Modeling Tools• PlanEditor.exe (Interactive)
Specify roles (e.g. input vs output) anddistributions for variables
• Dnet.exe (Command line)Build a dependency network or Bayesiannetwork from data
• DnetBrowser.exe (Interactive)Interactively browse dependency network orBayesian network
• DnetLogscore.exe (Command Line)Evaluate Prediction accuracy of models
![Page 5: The WinMine Toolkit Max Chickering. Build Statistical Models From Data Dependency Networks Bayesian Networks Local Distributions –Trees Multinomial](https://reader035.vdocuments.net/reader035/viewer/2022081700/56649eba5503460f94bc2ab0/html5/thumbnails/5.jpg)
Built-In Help: -help Option
c:\WinMine Toolkit\Bin>datacheck -helpThis executable parses a data file and prints outsummary statistics.
If a marginal statistics file is provided with the'-marg' flag, the executable collects marginal countsfor each variable and prints them to that file.
![Page 6: The WinMine Toolkit Max Chickering. Build Statistical Models From Data Dependency Networks Bayesian Networks Local Distributions –Trees Multinomial](https://reader035.vdocuments.net/reader035/viewer/2022081700/56649eba5503460f94bc2ab0/html5/thumbnails/6.jpg)
Built-In Help: No Arguments
c:\WinMine Toolkit\Bin>datacheckError in command line: required argument '-data' not givensyntax for datacheck:
Flag Type Description Optional? Default--------------------------------------------------------------data string Data file no-report string Report file yes-marg string Marginal counts file yes-silent bool Suppress progress output yes false-help bool Display help yes false
c:\WinMine Toolkit\Bin>
![Page 7: The WinMine Toolkit Max Chickering. Build Statistical Models From Data Dependency Networks Bayesian Networks Local Distributions –Trees Multinomial](https://reader035.vdocuments.net/reader035/viewer/2022081700/56649eba5503460f94bc2ab0/html5/thumbnails/7.jpg)
Interactive Mode
c:\WinMine Toolkit\Bin>datacheck -gui
![Page 8: The WinMine Toolkit Max Chickering. Build Statistical Models From Data Dependency Networks Bayesian Networks Local Distributions –Trees Multinomial](https://reader035.vdocuments.net/reader035/viewer/2022081700/56649eba5503460f94bc2ab0/html5/thumbnails/8.jpg)
WinMine Home Page:http://www.research.microsoft.com/~dmax/WinMine/Tooldoc.htm
• Download/Update toolsNo registry changes: simply copies executables
• Online TutorialSteps through using all of the tools with a simple example
• Discussion Group