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See searches and references containing MUTUAL INFORMATION!MUTUAL INFORMATION
Measure of dependence between two variables
In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two
Mutual_information
Information theory
particularly information theory, the conditional mutual information is, in its most basic form, the expected value of the mutual information of two random
Conditional mutual information
Conditional_mutual_information
Information Theory
statistics, probability theory and information theory, pointwise mutual information (PMI), or point mutual information, is a measure of association. It
Pointwise_mutual_information
Used to compare clustering when variation of mutual information is employed
In probability theory and information theory, adjusted mutual information, a variation of mutual information may be used for comparing clusterings. It
Adjusted_mutual_information
Measure in quantum information theory
In quantum information theory, quantum mutual information (QMI), or von Neumann mutual information, after John von Neumann, is a measure of correlation
Quantum_mutual_information
Topics referred to by the same term
derive a right to profits and votes Mutual information, the intersection of multiple information sets Mutual insurance, where policyholders have certain
Mutual
Scientific study of digital information
p(y)}}} where SI (Specific mutual Information) is the pointwise mutual information. A basic property of the mutual information is that: I ( X ; Y ) = H
Information_theory
Generalization of mutual information for more than two variables
interaction information, including amount of information, information correlation, co-information, and simply mutual information. Interaction information expresses
Interaction_information
Mathematical statistics distance measure
commonly used characterization of entropy. Consequently, mutual information is the only measure of mutual dependence that obeys certain related conditions, since
Kullback–Leibler_divergence
Statistical distance measure
,P_{n})\leq \log _{b}(n)} . The Jensen–Shannon divergence is the mutual information between a random variable X {\displaystyle X} associated to a mixture
Jensen–Shannon_divergence
Gain from observing another random variable
(In broader contexts, information gain can also be used as a synonym for either Kullback–Leibler divergence or mutual information, but the focus of this
Information gain (decision tree)
Information_gain_(decision_tree)
Measure of distance between two clusterings related to mutual information
closely related to mutual information; indeed, it is a simple linear expression involving the mutual information. Unlike the mutual information, however, the
Variation_of_information
Process in machine learning and statistics
of the feature set. Common measures include the mutual information, the pointwise mutual information, Pearson product-moment correlation coefficient,
Feature_selection
Facts provided or learned about something or someone
measures in information theory are mutual information, channel capacity, error exponents, and relative entropy. Important sub-fields of information theory
Information
Average uncertainty in variable's states
Kolmogorov–Sinai entropy in dynamical systems Levenshtein distance Mutual information Perplexity Qualitative variation – other measures of statistical dispersion
Entropy_(information_theory)
Thought experiment of 1867
fluctuation theorem with mutual information are satisfied. For more general information processes including biological information processing, both inequality
Maxwell's_demon
of the information content of random variables and a measure over sets. Namely the joint entropy, conditional entropy, and mutual information can be considered
Information theory and measure theory
Information_theory_and_measure_theory
Semantic similarity measure
In computational linguistics, second-order co-occurrence pointwise mutual information (SOC-PMI) is a method used to measure semantic similarity, or how
Second-order co-occurrence pointwise mutual information
Second-order_co-occurrence_pointwise_mutual_information
Generalization of the one-dimensional normal distribution to higher dimensions
Retrieved 2020-08-12. Proof: Mutual information of the multivariate normal distribution MacKay, David J. C. (2003-10-06). Information Theory, Inference and Learning
Multivariate normal distribution
Multivariate_normal_distribution
Upper bound on the knowable information of a quantum state
Define the accessible information between X {\displaystyle X} and Y {\displaystyle Y} as the (classical) mutual information between the two registers
Holevo's_theorem
Information-theoretical limit on transmission rate in a communication channel
of the channel, as defined above, is given by the maximum of the mutual information between the input and output of the channel, where the maximization
Channel_capacity
American multinational insurance company
Liberty Mutual Insurance Company, often referred to as Liberty Mutual Insurance, is an American diversified global insurer and the sixth-largest property
Liberty_Mutual
Concept in information processing
random, can increase the information that Y {\displaystyle Y} contains about X {\displaystyle X} . Using the mutual information, this can be written as :
Data_processing_inequality
Type of data encoding
The mutual information of PSK can be evaluated in additive Gaussian noise by numerical integration of its definition. The curves of mutual information saturate
Phase-shift_keying
Professionally managed investment fund
A mutual fund is an investment fund that pools money from many investors to purchase securities. The term is typically used in the United States, Canada
Mutual_fund
Grouping a set of objects by similarity
resulting clusters and the label used. The mutual information is an information theoretic measure of how much information is shared between a clustering and a
Cluster_analysis
and important measures of information is the mutual information, or transinformation. This is a measure of how much information can be obtained about one
Quantities_of_information
Venn diagram to illustrate relationship
entropy and mutual information. Information diagrams are a useful pedagogical tool for teaching and learning about these basic measures of information. Information
Information_diagram
Technique in information theory
condition to capture some fraction of the mutual information with the relevant variable Y. The information bottleneck can also be viewed as a rate distortion
Information_bottleneck_method
i − 1 ) {\displaystyle I(X^{i};Y_{i}|Y^{i-1})} is the conditional mutual information I ( X 1 , X 2 , . . . , X i ; Y i | Y 1 , Y 2 , . . . , Y i − 1 )
Directed_information
Notion in statistics
_{n}}}\right)\end{aligned}}} Similar to the entropy or mutual information, the Fisher information also possesses a chain rule decomposition. In particular
Fisher_information
ideas of the information entropy and redundancy of a source, and its relevance through the source coding theorem; the mutual information, and the channel
History_of_information_theory
Machine learning algorithm
expected information gain is the mutual information, meaning that on average, the reduction in the entropy of T is the mutual information. Information gain
Decision_tree_learning
Measure of relative information in probability theory
classical counterpart. Entropy (information theory) Mutual information Conditional quantum entropy Variation of information Entropy power inequality Likelihood
Conditional_entropy
Computer vision algorithm
transform, Pearson correlation (normalized cross-correlation). Even mutual information can be approximated as a sum over the pixels, and thus used as a local
Semi-global_matching
Message encoded with more bits than needed
{\displaystyle Y} , it is known that the joint mutual information can be less than the sum of the marginal mutual informations: I ( X 1 , X 2 ; Y ) < I ( X 1 ; Y
Redundancy (information theory)
Redundancy_(information_theory)
Decision tree training concept
into account when choosing an attribute. Information gain is also known as mutual information. Information gain is the reduction in entropy produced
Information_gain_ratio
Statistical relationship
generalized to other forms of association between two variables, such as mutual information and distance covariance. The most familiar measure of dependence between
Correlation
variable X 2 {\displaystyle X_{2}} , classical information theory can only describe the mutual information of the joint variable { X 1 , X 2 } {\displaystyle
Partial information decomposition
Partial_information_decomposition
Concept in information theory
as special cases of a single inequality involving the conditional mutual information, namely I ( A ; B | C ) ≥ 0 , {\displaystyle I(A;B|C)\geq 0,} where
Inequalities in information theory
Inequalities_in_information_theory
Estimate of the importance of a word in a document
Latent semantic analysis Mutual information Noun phrase Okapi BM25 PageRank Vector space model Word count SMART Information Retrieval System Rajaraman
Tf–idf
Statistical measure of association between variables
studies published on arXiv. The maximal information coefficient uses binning as a means to apply mutual information on continuous random variables. Binning
Maximal information coefficient
Maximal_information_coefficient
Information-theoretic measure
divergence Maximum-likelihood estimation Mutual information Perplexity Thomas M. Cover, Joy A. Thomas, Elements of Information Theory, 2nd Edition, Wiley, p. 80
Cross-entropy
Kth smallest value in a statistical sample
the CLT, our results follow by application of the delta method. The mutual information and f-divergence between order statistics have also been considered
Order_statistic
in particular in information theory, total correlation (Watanabe 1960) is one of several generalizations of the mutual information. It is also known
Total_correlation
Doctrine of military strategy
Mutually assured destruction or mutual assured destruction (MAD) is a doctrine of military strategy and national security policy which posits that a full-scale
Mutually_assured_destruction
Mathematical analysis of gambling
with whatever side information we are able to obtain. The value of this "illicit" side information is measured as mutual information relative to the outcome
Gambling and information theory
Gambling_and_information_theory
American radio broadcasting network (1934–1999)
The Mutual Broadcasting System (commonly referred to simply as Mutual; sometimes referred to as MBS, Mutual Radio or the Mutual Radio Network) was an
Mutual_Broadcasting_System
application to pattern recognition and psychology. Mutual Information Total Correlation Interaction information Garner W R (1962). Uncertainty and Structure
Constraint (information theory)
Constraint_(information_theory)
theoretical formulation based on mutual information, along with the first definition of multivariate mutual information, published in IEEE Trans. Pattern
Minimum redundancy feature selection
Minimum_redundancy_feature_selection
Optimization principle for artificial neural networks
should be chosen or learned so as to maximize the average Shannon mutual information between x {\displaystyle x} and z ( x ) {\displaystyle z(x)} , subject
Infomax
Two parties authenticating each other at the same time
Mutual authentication or two-way authentication is the simultaneous and reciprocal authentication of two parties. It is part of authentication protocols
Mutual_authentication
Treaty to enforce public or criminal laws
A mutual legal assistance treaty (MLAT) is an agreement between two or more countries for the purpose of gathering and exchanging information in an effort
Mutual legal assistance treaty
Mutual_legal_assistance_treaty
Entropy measure
quantum information in the state will remain after the state goes through the channel. In this sense, it is intuitively similar to the mutual information of
Coherent_information
Statistical test
value of the G-test statistics can also be expressed in terms of mutual information. In this case objects with two-dimensional types ( i , j ) {\displaystyle
G-test
Theorem that tells the maximum rate at which information can be transmitted
In information theory, the Shannon–Hartley theorem tells the maximum rate at which information can be transmitted over a communications channel of a specified
Shannon–Hartley_theorem
American bank holding company (1889–2008)
Washington Mutual, Inc. (often abbreviated to WaMu) was an American savings bank holding company based in Seattle. It was the parent company of Washington
Washington_Mutual
Graph measuring gene relationships
with blood sugar). Butte and Kohane used this approach later with mutual information as the co-expression measure and using gene expression data for constructing
Gene_co-expression_network
Quantity in information theory
self-information above is not universal. Since the notation I ( X ; Y ) {\displaystyle I(X;Y)} is also often used for the related quantity of mutual information
Information_content
British mutual insurance company
NFU Mutual is a UK insurance company. It is a mutual business, meaning that the policyholder members own the business, and the executives and directors
NFU_Mutual
Measure of similarity between samples
alternative to other similarity metrics, such as Pearson correlation or mutual information. Here we find the biweight midcorrelation of two vectors x {\displaystyle
Biweight_midcorrelation
Information known by all participatory agents
Mutual knowledge in game theory is information known by all participatory agents. However, unlike common knowledge, a related topic, mutual knowledge
Mutual_knowledge
Measure of information in probability and information theory
(X)+\mathrm {H} (Y|X)} . Joint entropy is also used in the definition of mutual information I ( X ; Y ) = H ( X ) + H ( Y ) − H ( X , Y ) {\displaystyle \operatorname
Joint_entropy
Theory about lossy data compression
{\displaystyle X} , and I Q ( Y ; X ) {\displaystyle I_{Q}(Y;X)} is the mutual information between Y {\displaystyle Y} and X {\displaystyle X} defined as I (
Rate–distortion_theory
described using measures like a massive correlation or mutual information. Co-occurrence information and knowledge of co-occurring words may be relevant
Co-occurrence
Phenomenon in statistics
cell frequencies. The proposed shrinkage estimators of entropy and mutual information, as well as all other investigated entropy estimators, have been implemented
Shrinkage_(statistics)
Limit on data transfer rate
memoryless channel, the channel capacity, defined in terms of the mutual information I ( X ; Y ) {\displaystyle I(X;Y)} as C = sup p X I ( X ; Y ) {\displaystyle
Noisy-channel_coding_theorem
Field of linguistics
(size, extension, etc.) Frequency weighting (e.g. entropy, pointwise mutual information, etc.) Dimension reduction (e.g. random indexing, singular value decomposition
Distributional_semantics
introduction of a mutual fund in India occurred in 1963, when the Government of India launched the Unit Trust of India (UTI). Mutual funds are broadly
Mutual_funds_in_India
Topics referred to by the same term
Neischnocolus Acute myocardial infarction, a heart attack Adjusted mutual information, in information theory Advanced metering infrastructure, for energy smart
Ami
Measure of dependence
information is one of several known non-negative generalizations of mutual information. While total correlation is bounded by the sum entropies of the n
Dual_total_correlation
Concept in information theory
\alpha =1} quantities allow the definition of conditional information and mutual information from communication theory. The Rényi entropies and divergences
Rényi_entropy
where I ( X i ; X j ( i ) ) {\displaystyle I(X_{i};X_{j(i)})} is the mutual information between variable X i {\displaystyle X_{i}} and its parent X j ( i
Chow–Liu_tree
or organism) when an appropriate measure of information transfer (signal-to-noise ratio, mutual information, coherence, d', etc.) is maximized in the presence
Stochastic resonance (sensory neurobiology)
Stochastic_resonance_(sensory_neurobiology)
Determination of language from a text sample
compressibility of texts in a set of known languages. This approach is known as mutual information based distance measure. The same technique can also be used to empirically
Language_identification
Concept in information theory
significance as a measure of discrete information since it is actually the limit of the discrete mutual information of partitions of X {\displaystyle X}
Differential_entropy
Japanese insurance company
Asahi Mutual Life Insurance Company (朝日生命保険相互会社, Asahi Seimei Hoken Sōgo-kaisha) is a Japanese insurance company, headquartered in Tokyo. The company was
Asahi_Life
Closeness of linguistic varieties
varieties are mutually intelligible, but differences mount with distance, so that more widely separated varieties may not be mutually intelligible. Intelligibility
Mutual_intelligibility
Relationship of various quantum subsystems
BC)\leq S(A\mid B)} . This can also be restated in terms of quantum mutual information, I ( A : B C ) ≥ I ( A : B ) {\displaystyle I(A:BC)\geq I(A:B)} .
Strong subadditivity of quantum entropy
Strong_subadditivity_of_quantum_entropy
Time density of the average information in a stochastic process
the entropy rate or source information rate of a stochastic process is, informally, the time density of the average information in a stochastic process.
Entropy_rate
Term in information theory
Shannon's entropy and differential entropy, as one could find the mutual information I ( X ; Y ) {\displaystyle I(X;Y)} using the following formula: I
Information_dimension
Mapping of data into a single system
cross-correlation, mutual information, sum of squared intensity differences, and ratio image uniformity. Mutual information and normalized mutual information are the
Image_registration
Topics referred to by the same term
for: Pointwise mutual information, in statistics Privilege Management Infrastructure in cryptography Product and manufacturing information in CAD systems
PMI
American mutual life insurance company
The Massachusetts Mutual Life Insurance Company, also known as MassMutual, is an American life insurance company. MassMutual provides financial products
MassMutual
Non-parametric statistic on information transfer
entropy measures such as Rényi entropy. Transfer entropy is conditional mutual information, with the history of the influenced variable Y t − 1 : t − L {\displaystyle
Transfer_entropy
Use of the second law of thermodynamics to distinguish past from future
a decreasing mutual entropy (or increasing mutual information), and for a time that is not too long—the correlations (mutual information) between particles
Entropy_as_an_arrow_of_time
State-dependent measures that converge to the mutual information
state-dependent measures that in expectation converge to the mutual information. State-dependent informations often appear in neuroscience applications. Let X {\displaystyle
State-dependent_information
images that have an intensity linear relationship Mutual information (AdvancedMattesMutualInformation) to be used for both mono- and multi-modal applications
Elastix_(image_registration)
Measure of nonclassical correlations between two subsystems of a quantum system
mathematical terms, quantum discord is defined in terms of the quantum mutual information. More specifically, quantum discord is the difference between two
Quantum_discord
Measure of "category goodness"
to the information gain metric used in decision tree learning. In certain presentations, it is also formally equivalent to the mutual information, as discussed
Category_utility
2010 book by Serbian Vlatko Vedral
buying gym membership to help motivated self win over lazy self. Mutual information resulting in phase transitions in social and political demography
Decoding_Reality
expression makes clear that the uncertainty coefficient is a normalised mutual information I(X;Y). In particular, the uncertainty coefficient ranges in [0, 1]
Uncertainty_coefficient
Signal processing computational method
independence for ICA are Minimization of mutual information Maximization of non-Gaussianity The Minimization-of-Mutual information (MMI) family of ICA algorithms
Independent component analysis
Independent_component_analysis
divergence / (2:DCR) Mutual information / (23F:DC) Copula / (2F:C) Cramér's theorem / (2:C) Kullback–Leibler divergence / (2:DCR) Mutual information / (23F:DC)
Catalog of articles in probability theory
Catalog_of_articles_in_probability_theory
inferring protein residue contacts using correlation measures like mutual information. The inference of the Potts model on a multiple sequence alignment
Direct_coupling_analysis
Computational technique to find word sequences
calculate a score associated to every word pairs. Proposed formulas are mutual information, t-test, z test, chi-squared test and likelihood ratio. Within the
Collocation_extraction
Problem in natural language processing and information retrieval
probability theory and information theory, mutual information measures the degree of dependence of two random variables. The mutual information of two variables
Cluster_labeling
Japanese mathematician
coherent information, though each of them plays important role in quantum information theory. The information theoretic meaning of Ohya's quantum mutual information
Masanori_Ohya
discretizing continuous data include Fayyad & Irani's MDL method, which uses mutual information to recursively define the best bins, CAIM, CACC, Ameva, and many others
Discretization of continuous features
Discretization_of_continuous_features
Indian bank sponsored fund house
Mutual Fund in the mutual fund sector are Axis Mutual Fund, Birla Sun Life Mutual Fund, HDFC Mutual Fund, ICICI Prudential Mutual Fund, Kotak Mutual Fund
SBI_Mutual_Fund
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