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ACL
1996
13 years 6 months ago
Compilation of Weighted Finite-State Transducers from Decision Trees
We report on a method for compiling decision trees into weighted finite-state transducers. The key assumptions are that the tree predictions specify how to rewrite symbols from an...
Richard Sproat, Michael Riley
AUSDM
2008
Springer
258views Data Mining» more  AUSDM 2008»
13 years 6 months ago
wFDT - Weighted Fuzzy Decision Trees for Prognosis of Breast Cancer Survivability
Accurate and less invasive personalized predictive medicine can spare many breast cancer patients from receiving complex surgical biopsies, unnecessary adjuvant treatments and its...
Umer Khan, Hyunjung Shin, Jongpill Choi, Minkoo Ki...
ICLP
1992
Springer
13 years 9 months ago
Weighted Decision Trees
: Whiledecision tree compilationis a promisingway tocarry out guard tests e ciently, the methods given in the literature do not take into account either the execution characteristi...
Saumya K. Debray, Sampath Kannan, Mukul Paithane
ISCI
2008
124views more  ISCI 2008»
13 years 4 months ago
A weighted rough set based method developed for class imbalance learning
In this paper, we introduce weights into Pawlak rough set model to balance the class distribution of a data set and develop a weighted rough set based method to deal with the clas...
Jinfu Liu, Qinghua Hu, Daren Yu
APPROX
2008
Springer
245views Algorithms» more  APPROX 2008»
13 years 6 months ago
Approximating Optimal Binary Decision Trees
Abstract. We give a (ln n + 1)-approximation for the decision tree (DT) problem. An instance of DT is a set of m binary tests T = (T1, . . . , Tm) and a set of n items X = (X1, . ....
Micah Adler, Brent Heeringa