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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AdaBoostAffective computingAlternating decision treeBootstrap aggregating
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Papers overview

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2014
2014
DECISION TREE LEARNING
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
Region-based image retrieval with high-level semantics using decision tree learning
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
A Fast Decision Tree Learning Algorithm
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
The Foundations of Cost-Sensitive Learning
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 Alternating Decision Tree Learning Algorithm
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
Fuzzy decision trees: issues and methods
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
Statistical Decision-Tree Models for Parsing
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
Multivariate decision trees
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
A comparison of two learning algorithms for text categorization
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
Using Decision Trees to Improve Case-Based Learning
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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