Categorical variable

Known as: Categorical, Categorical data, Nonnumerical variable 
In statistics, a categorical variable is a variable that can take on one of a limited, and usually fixed, number of possible values, assigning each… (More)
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Topic mentions per year

Topic mentions per year

1955-2018
05010015019552017

Papers overview

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Highly Cited
2011
Highly Cited
2011
This course introduces principles and analyses related to data with categorical outcomes. This course will consider topics such… (More)
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Highly Cited
2007
Highly Cited
2007
Uncertainty in categorical data is commonplace in many applications, including data cleaning, database integration, and… (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 categorical… (More)
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Highly Cited
2006
Highly Cited
2006
Privacy becomes a more and more serious concern in applications involving microdata. Recently, efficient anonymization has… (More)
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Highly Cited
2005
Highly Cited
2005
We consider the following problem: given a set of clusterings, find a single clustering that agrees as much as possible with the… (More)
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Highly Cited
2002
Highly Cited
2002
In this paper we explore the connection between clustering categorical data and entropy: clusters of similar poi lower entropy… (More)
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Highly Cited
1999
Highly Cited
1999
Graphical methods for quantitative data are well-developed, and widely used in both data analysis (e.g., detecting outliers… (More)
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Highly Cited
1999
Highly Cited
1999
This correspondence describes extensions to the fuzzy k-means algorithm for clustering categorical data. By using a simple… (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 have… (More)
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Highly Cited
1998
Highly Cited
1998
The k-means algorithm is well known for its efficiency in clustering large data sets. However, working only on numeric values… (More)
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