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Decision tree learning
Known as:
Gini impurity
, Regression tree
, CART
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Decision tree learning uses a decision tree as a predictive model which maps observations about an item (represented in the branches) to conclusions…
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Related topics
Related topics
50 relations
AdaBoost
Affective computing
Alternating decision tree
Bootstrap aggregating
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2010
Highly Cited
2010
Discrimination Aware Decision Tree Learning
F. Kamiran
,
T. Calders
,
Mykola Pechenizkiy
IEEE International Conference on Data Mining
2010
Corpus ID: 2404158
Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute B…
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Highly Cited
2009
Highly Cited
2009
Stochastic gradient boosted distributed decision trees
Jerry Ye
,
J. Chow
,
Jiang Chen
,
Zhaohui Zheng
CIKM
2009
Corpus ID: 269038
Stochastic Gradient Boosted Decision Trees (GBDT) is one of the most widely used learning algorithms in machine learning today…
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Highly Cited
2007
Highly Cited
2007
Data Mining with Decision Trees - Theory and Applications
L. Rokach
,
O. Maimon
Series in Machine Perception and Artificial…
2007
Corpus ID: 21343600
Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the…
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Highly Cited
2006
Highly Cited
2006
A Fast Decision Tree Learning Algorithm
Jiang Su
,
Harry Zhang
AAAI
2006
Corpus ID: 2128098
There is growing interest in scaling up the widely-used decision-tree learning algorithms to very large data sets. Although…
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Review
2005
Review
2005
Top-down induction of decision trees classifiers - a survey
L. Rokach
,
O. Maimon
IEEE Transactions on Systems, Man, and…
2005
Corpus ID: 14808716
Decision trees are considered to be one of the most popular approaches for representing classifiers. Researchers from various…
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Review
2004
Review
2004
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Sreerama K. Murthy
Data Mining and Knowledge Discovery
2004
Corpus ID: 207741345
Decision trees have proved to be valuable tools for the description, classification and generalization of data. Work on…
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Highly Cited
2004
Highly Cited
2004
Failure diagnosis using decision trees
Mike Y. Chen
,
A. Zheng
,
J. Lloyd
,
Michael I. Jordan
,
E. Brewer
2004
Corpus ID: 56849250
We present a decision tree learning approach to diagnosing failures in large Internet sites. We record runtime properties of each…
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Highly Cited
1999
Highly Cited
1999
The Alternating Decision Tree Learning Algorithm
Y. Freund
,
L. Mason
ICML
1999
Corpus ID: 3772657
The application of boosting procedures to decision tree algorithms has been shown to produce very accurate classi ers. These…
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Highly Cited
1995
Highly Cited
1995
Statistical Decision-Tree Models for Parsing
David M. Magerman
ACL
1995
Corpus ID: 608
Syntactic natural language parsers have shown themselves to be inadequate for processing highly-ambiguous large-vocabulary text…
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Highly Cited
1995
Highly Cited
1995
Robust Decision Trees: Removing Outliers from Databases
George H. John
KDD
1995
Corpus ID: 2884977
Finding and removing outliers is an important problem in data mining. Errors in large databases can be extremely common, so an…
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