1 / 10

Datamining in e-Business: Veni, Vidi, Vici!

Datamining in e-Business: Veni, Vidi, Vici!. by Prof. Dr. Veljko Milutinovic. THIS IS A DEMO VERSION OF THE TUTORIAL IN DATAMINING FOR E-BUSINESS. ONLY A FEW SLIDES OF THE ORIGINAL TUTORIAL ARE PRESENTED HERE. Focus of this Presentation. Data Mining problem types.

javier
Download Presentation

Datamining in e-Business: Veni, Vidi, Vici!

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Datamining in e-Business: Veni, Vidi, Vici! by Prof. Dr. Veljko Milutinovic

  2. THIS IS A DEMO VERSION OF THE TUTORIAL IN DATAMINING FOR E-BUSINESS ONLY A FEW SLIDES OF THE ORIGINAL TUTORIAL ARE PRESENTED HERE

  3. Focus of this Presentation • Data Mining problem types • Data Mining models and algorithms • Efficient Data Mining • Available software

  4. Decision Trees Balance>10 Balance<=10 Age<=32 Age>32 Married=NO Married=YES

  5. Decision Trees

  6. Rule Induction • Method of deriving a set of rules to classify cases • Creates independent rules that are unlikely to form a tree • Rules may not cover all possible situations • Rules may sometimes conflict in a prediction

  7. Comparison of fourteen DM tools • Evaluated by four undergraduates inexperienced at data mining, a relatively experienced graduate student, and a professional data mining consultant • Run under the MS Windows 95, MS Windows NT, Macintosh System 7.5 • Use one of the four technologies: Decision Trees, Rule Inductions, Neural, or Polynomial Networks • Solve two binary classification problems: multi-class classification and noiseless estimation problem • Price from 75$ to 25.000$

  8. Comparison of fourteen DM tools • The Decision Tree products were - CART - Scenario - See5 - S-Plus • The Rule Induction tools were - WizWhy - DataMind - DMSK • Neural Networks were built from three programs - NeuroShell2 - PcOLPARS - PRW • The Polynomial Network tools were - ModelQuest Expert - Gnosis - a module of NeuroShell2 - KnowledgeMiner

  9. Criteria for evaluating DM tools A list of 20 criteria for evaluating DM tools, put into 4 categories: • Capability measures what a desktop tool can do, and how well it does it - Handlesmissing data - - Considers misclassification costs - Allows data transformations - Includes quality of tesing options - Has a programming language - Provides useful output reports - Provides visualisation

  10. Criteria for evaluating DM tools • Interoperability shows a tool’s ability to interface with other computer applications - Importing data - Exporting data - Links to other applications • Flexibility - Model adjustment flexibility - Customizable work enviroment - Ability to write or change code

More Related