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28 relations: Anomaly detection, Bayes' theorem, Bernard Silverman, Blood plasma, Cluster analysis, Conditional probability, Data, Data set, Diabetes mellitus, Estimation, Glucose, Histogram, Kernel density estimation, Kernel embedding of distributions, Mean, Mean integrated squared error, Multivariate kernel density estimation, Pima people, Probability, Probability density function, R (programming language), Robert Tibshirani, Spectral density estimation, Statistics, Trevor Hastie, Variable kernel density estimation, Vector quantization, World Health Organization.
Anomaly detection
In data mining, anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset.
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Bayes' theorem
In probability theory and statistics, Bayes’ theorem (alternatively Bayes’ law or Bayes' rule, also written as Bayes’s theorem) describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
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Bernard Silverman
Sir Bernard Walter Silverman, (born 22 February 1952) is a British statistician and Anglican Priest.
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Blood plasma
Blood plasma is a yellowish coloured liquid component of blood that normally holds the blood cells in whole blood in suspension; this makes plasma the extracellular matrix of blood cells.
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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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Conditional probability
In probability theory, conditional probability is a measure of the probability of an event (some particular situation occurring) given that (by assumption, presumption, assertion or evidence) another event has occurred.
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Data
Data is a set of values of qualitative or quantitative variables.
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Data set
A data set (or dataset) is a collection of data.
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Diabetes mellitus
Diabetes mellitus (DM), commonly referred to as diabetes, is a group of metabolic disorders in which there are high blood sugar levels over a prolonged period.
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Estimation
Estimation (or estimating) is the process of finding an estimate, or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable.
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Glucose
Glucose is a simple sugar with the molecular formula C6H12O6.
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Histogram
A histogram is an accurate representation of the distribution of numerical data.
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Kernel density estimation
In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable.
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Kernel embedding of distributions
In machine learning, the kernel embedding of distributions (also called the kernel mean or mean map) comprises a class of nonparametric methods in which a probability distribution is represented as an element of a reproducing kernel Hilbert space (RKHS).
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Mean
In mathematics, mean has several different definitions depending on the context.
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Mean integrated squared error
In statistics, the mean integrated squared error (MISE) is used in density estimation.
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Multivariate kernel density estimation
Kernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the fundamental questions in statistics.
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Pima people
The Pima (or Akimel O'odham, also spelled Akimel O'otham, "River People", formerly known as Pima) are a group of Native Americans living in an area consisting of what is now central and southern Arizona.
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Probability
Probability is the measure of the likelihood that an event will occur.
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Probability density function
In probability theory, a probability density function (PDF), or density of a continuous random variable, is a function, whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would equal that sample.
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R (programming language)
R is a programming language and free software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing.
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Robert Tibshirani
Robert Tibshirani (born July 10, 1956) is a Professor in the Departments of Statistics and Health Research and Policy at Stanford University.
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Spectral density estimation
In statistical signal processing, the goal of spectral density estimation (SDE) is to estimate the spectral density (also known as the power spectral density) of a random signal from a sequence of time samples of the signal.
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Statistics
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.
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Trevor Hastie
Trevor John Hastie (born 27 June 1953) is a South African and American statistician and computer scientist.
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Variable kernel density estimation
In statistics, adaptive or "variable-bandwidth" kernel density estimation is a form of kernel density estimation in which the size of the kernels used in the estimate are varied depending upon either the location of the samples or the location of the test point.
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Vector quantization
Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors.
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World Health Organization
The World Health Organization (WHO; French: Organisation mondiale de la santé) is a specialized agency of the United Nations that is concerned with international public health.
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References
[1] https://en.wikipedia.org/wiki/Density_estimation
