Data mining on a mushroom database
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“Data Mining on a Mushroom Database”. Clara Eusebi, Cosmin Gilga, Deepa John, Andre Maisonave. Presentation Summary. Background Concepts Literature Review Focus of Study Research Methodology Results of Study Mushroom Database Application Future Research Conclusions. Background.

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Data mining on a mushroom database

“Data Mining on a Mushroom Database”

Clara Eusebi,

Cosmin Gilga,

Deepa John,

Andre Maisonave


Presentation summary
Presentation Summary

  • Background Concepts

  • Literature Review

  • Focus of Study

  • Research Methodology

  • Results of Study

  • Mushroom Database Application

  • Future Research

  • Conclusions


Background
Background

  • Algorithms and Techniques

  • Jeff Schlimmer’s Dissertation

  • Confusion Matrix


Literature review
Literature Review

  • Overview of Data Mining

  • Decision Trees

  • Visual Classification and Human-Machine Interaction


Focus of the study
Focus of the Study

  • Run algorithms in Weka on the Mushroom Database

  • Mushroom Database Application

  • Edible or Poisonous?


Research methodology
Research Methodology

  • Unpruned decision tree

  • Classifiers that do not generate rules

  • A classifier that does generate rules

  • Jeff Schlimmer’s optimal rule set


Results of the study
Results of the Study

  • Results on client databases

    • much higher accuracy

  • Results on Schlimmer’s database

    • Elaborate unpruned tree


Mushroom database application
Mushroom Database Application

  • Available at:

    http://utopia.csis.pace.edu/cs691/2007-2008/team6/Mushroom_Database_Application.html


Future research
Future Research

  • Differences between Dr. Cha’s data and Schlimmer’s data


Conclusions
Conclusions

  • J48 Unpruned Tree

    • Highest accuracy results

  • Mushroom Database Application

    • Human-Machine Interaction


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