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11 relations: Cluster analysis, Contingency table, Entropy (information theory), Hypergeometric distribution, Information theory, Mutual information, Partition of a set, Probability theory, Rand index, Similarity measure, Variation of information.
Cluster analysis
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters).
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Contingency table
In statistics, a contingency table (also known as a cross tabulation or crosstab) is a type of table in a matrix format that displays the (multivariate) frequency distribution of the variables.
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Entropy (information theory)
Information entropy is the average rate at which information is produced by a stochastic source of data.
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Hypergeometric distribution
In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of k successes (random draws for which the object drawn has a specified feature) in n draws, without replacement, from a finite population of size N that contains exactly K objects with that feature, wherein each draw is either a success or a failure.
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Information theory
Information theory studies the quantification, storage, and communication of information.
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Mutual information
In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables.
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Partition of a set
In mathematics, a partition of a set is a grouping of the set's elements into non-empty subsets, in such a way that every element is included in one and only one of the subsets.
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Probability theory
Probability theory is the branch of mathematics concerned with probability.
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Rand index
The Rand index or Rand measure (named after William M. Rand) in statistics, and in particular in data clustering, is a measure of the similarity between two data clusterings.
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Similarity measure
In statistics and related fields, a similarity measure or similarity function is a real-valued function that quantifies the similarity between two objects.
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Variation of information
In probability theory and information theory, the variation of information or shared information distance is a measure of the distance between two clusterings (partitions of elements).
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References
[1] https://en.wikipedia.org/wiki/Adjusted_mutual_information
