The document discusses the development of a linear machine learning algorithm for building a decision tree as an accurate classifier. It emphasizes eliminating unnecessary variables and obtaining a compact tree through a combination of decision tree learning and linear discriminate functions. Ultimately, the goal is to create a more efficient classification algorithm.

1. Linear Machine Decision Tree
Ashis Kumar Chanda
Utgof & Brodley(1991)
Department of Computer Science and Engineering
University of Dhaka
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2. Objective
• Building a decision tree to obtain an accurate
classifier
• Develop a linear machine
• Eliminate variable
• Make a compact tree
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3. Overview
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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
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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
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6. Correction of c
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7. Variable Elimination
• Develop a tree that does not evaluate
unnecessary variable
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9. Conclusion
• Proposed an linear machine learning
algorithm to generate a tree in classification
algorithm
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10. Reference
• Linear Machine Decision Tree, by Utgof &
Brodley (1991)
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