Monotone Decision Trees and Noisy Data
2002-06-17
Research Paper
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The decision tree algorithm for monotone classification presented in [4, 10] requires strictly monotone data sets. This paper addresses the problem of noise due to violation of the monotonicity constraints and proposes a modification of the algorithm to handle noisy data. It also presents methods for controlling the size of the resulting trees while keeping the monotonicity property whether the data set is monotone or not.
Keywords
Classifications using
Journal of Economic Literature (JEL) Classification System
- C6 : Mathematical Methods and Programming
- M : Business Administration and Business Economics; Marketing; Accounting
- R4 : Transportation Systems
- M11 : Production Management
Automatically Extracted Terms
- management
- classification
- research
- business
- report
- decision trees
- data jan c
- series
- decision
- bioch
- system
- monotonicity
- van der made-potuijt
- value sajda qureshi
- rotterdam
- roodbergen ers -2002-19-lis
- report series research
- programming business administration
- process
- paradigm saskia c
