In statistics, a categorical variable is a variable that can take on one of a limited, and usually fixed, number of possible values, assigning eachâ€¦Â (More)

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Highly Cited

2011

Highly Cited

2011

- Alan Agresti, Maria Kateri
- International Encyclopedia of Statistical Science
- 2011

This course introduces principles and analyses related to data with categorical outcomes. This course will consider topics suchâ€¦Â (More)

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Highly Cited

2007

Highly Cited

2007

- Sarvjeet Singh, Chris Mayfield, Sunil Prabhakar, Rahul Shah, Susanne E. Hambrusch
- 2007 IEEE 23rd International Conference on Dataâ€¦
- 2007

Uncertainty in categorical data is commonplace in many applications, including data cleaning, database integration, andâ€¦Â (More)

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Highly Cited

2006

Highly Cited

2006

- R. Gll Pontlus
- 2006

This paper analyzes quantification error versus location error in a comparison between two cellular maps that show a categoricalâ€¦Â (More)

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Highly Cited

2006

Highly Cited

2006

- Jian Xu, Wei Wang, Jian Pei, Xiaoyuan Wang, Baile Shi, Ada Wai-Chee Fu
- KDD
- 2006

Privacy becomes a more and more serious concern in applications involving microdata. Recently, efficient anonymization hasâ€¦Â (More)

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Highly Cited

2005

Highly Cited

2005

- Aristides Gionis, Heikki Mannila, Panayiotis Tsaparas
- 21st International Conference on Data Engineeringâ€¦
- 2005

We consider the following problem: given a set of clusterings, find a single clustering that agrees as much as possible with theâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

- Daniel BarbarÃ¡, Yi Li, Julia Couto
- CIKM
- 2002

In this paper we explore the connection between clustering categorical data and entropy: clusters of similar poi lower entropyâ€¦Â (More)

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Highly Cited

1999

Highly Cited

1999

- Michael Friendly
- 1999

Graphical methods for quantitative data are well-developed, and widely used in both data analysis (e.g., detecting outliersâ€¦Â (More)

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Highly Cited

1999

Highly Cited

1999

- Joshua Zhexue Huang, Michael K. Ng
- IEEE Trans. Fuzzy Systems
- 1999

This correspondence describes extensions to the fuzzy k-means algorithm for clustering categorical data. By using a simpleâ€¦Â (More)

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Highly Cited

1999

Highly Cited

1999

Clustering is an important data mining problem. Most of the earlier work on clustering focussed on numeric attributes which haveâ€¦Â (More)

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Highly Cited

1998

Highly Cited

1998

- Joshua Zhexue Huang
- Data Mining and Knowledge Discovery
- 1998

The k-means algorithm is well known for its efficiency in clustering large data sets. However, working only on numeric valuesâ€¦Â (More)

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