Decision tree learning

Known as: Gini impurity, Regression tree, CART 
Decision tree learning uses a decision tree as a predictive model which maps observations about an item (represented in the branches) to conclusions… (More)
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Papers overview

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2014
2014
TDIDF(D,cdef) • IF(all examples in D have same class c) – Return leaf with class c (or class cdef, if D is empty) • ELSE IF(no… (More)
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Highly Cited
2008
Highly Cited
2008
Semantic-based image retrieval has attracted great interest in recent years. This paper proposes a region-based image retrieval… (More)
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Review
2006
Review
2006
There is growing interest in scaling up the widely-used decision-tree learning algorithms to very large data sets. Although… (More)
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Highly Cited
2001
Highly Cited
2001
This paper revisits the problem of optimal learning and decision-making when different misclassification errors incur different… (More)
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Highly Cited
1999
Highly Cited
1999
The application of boosting procedures to decision tree algorithms has been shown to produce very accurate classi ers. These… (More)
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Highly Cited
1998
Highly Cited
1998
Decision trees are one of the most popular choices for learning and reasoning from feature-based examples. They have undergone a… (More)
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Highly Cited
1995
Highly Cited
1995
Syntactic natural language parsers have shown themselves to be inadequate for processing highly-ambiguous large-vocabulary text… (More)
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Highly Cited
1995
Highly Cited
1995
Unlike a univariate decision tree, a multivariate decision tree is not restricted to splits of the instance space that are… (More)
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Highly Cited
1994
Highly Cited
1994
This paper examines the use of inductive learning to categorize natural language documents into predeened content categories… (More)
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Highly Cited
1993
Highly Cited
1993
This paper shows that decision trees can be used to improve the performance of case-based learning (CBL) systems. We introduce a… (More)
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