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Linear Machine Decision Tree 
Ashis Kumar Chanda 
Utgof & Brodley(1991) 
Department of Computer Science and Engineering 
University of Dhaka 
1 I NAME OF PRESENTER
Objective 
• Building a decision tree to obtain an accurate 
classifier 
• Develop a linear machine 
• Eliminate variable 
• Make a compact tree 
2 CSE, DU 
2 I NAME OF PRESENTER
Overview 
3 CSE, DU 
3 I NAME OF PRESENTER
Linear machine 
• a linear machine is a program that itself 
classifies the instance 
Combination of two methods 
• Learning decision trees 
• Learning linear discriminate function 
4 CSE, DU 
4 I NAME OF PRESENTER
How train Linear Machine 
• Each instance is represented as a vector Y 
= 
W is a vector of adjustable coefficients 
c is the sufficient amount of correction is needed to cause 
linear machine become correct work 
CSE, DU 5
Correction of c 
CSE, DU 6
Variable Elimination 
• Develop a tree that does not evaluate 
unnecessary variable 
CSE, DU 7
CSE, DU 8
Conclusion 
• Proposed an linear machine learning 
algorithm to generate a tree in classification 
algorithm 
CSE, DU 9
Reference 
• Linear Machine Decision Tree, by Utgof & 
Brodley (1991) 
10 CSE, DU 
10 I NAME OF PRESENTER
11 11CISE, DU NAME OF PRESENTER
12 12CISE, DU NAME OF PRESENTER

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Linear Machine Decision Tree

  • 1. Linear Machine Decision Tree Ashis Kumar Chanda Utgof & Brodley(1991) Department of Computer Science and Engineering University of Dhaka 1 I NAME OF PRESENTER
  • 2. Objective • Building a decision tree to obtain an accurate classifier • Develop a linear machine • Eliminate variable • Make a compact tree 2 CSE, DU 2 I NAME OF PRESENTER
  • 3. Overview 3 CSE, DU 3 I NAME OF PRESENTER
  • 4. Linear machine • a linear machine is a program that itself classifies the instance Combination of two methods • Learning decision trees • Learning linear discriminate function 4 CSE, DU 4 I NAME OF PRESENTER
  • 5. How train Linear Machine • Each instance is represented as a vector Y = W is a vector of adjustable coefficients c is the sufficient amount of correction is needed to cause linear machine become correct work CSE, DU 5
  • 6. Correction of c CSE, DU 6
  • 7. Variable Elimination • Develop a tree that does not evaluate unnecessary variable CSE, DU 7
  • 9. Conclusion • Proposed an linear machine learning algorithm to generate a tree in classification algorithm CSE, DU 9
  • 10. Reference • Linear Machine Decision Tree, by Utgof & Brodley (1991) 10 CSE, DU 10 I NAME OF PRESENTER
  • 11. 11 11CISE, DU NAME OF PRESENTER
  • 12. 12 12CISE, DU NAME OF PRESENTER