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» Algorithms for optimal dyadic decision trees
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133
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JMLR
2002
102views more  JMLR 2002»
15 years 3 months ago
Efficient Algorithms for Decision Tree Cross-validation
Cross-validation is a useful and generally applicable technique often employed in machine learning, including decision tree induction. An important disadvantage of straightforward...
Hendrik Blockeel, Jan Struyf
124
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ICPR
2008
IEEE
15 years 10 months ago
Online adaptive clustering in a decision tree framework
We present an online adaptive clustering algorithm in a decision tree framework which has an adaptive tree and a code formation layer. The code formation layer stores the represen...
Jayanta Basak
181
Voted
SIGIR
2011
ACM
14 years 6 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
APPROX
2008
Springer
245views Algorithms» more  APPROX 2008»
15 years 5 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
114
Voted
AAAI
2006
15 years 4 months ago
When a Decision Tree Learner Has Plenty of Time
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch