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22 relations: Artificial intelligence, Bilinear form, Cluster analysis, Covariance, Hash function, Identity of indiscernibles, K-nearest neighbors algorithm, Large margin nearest neighbor, Latent semantic analysis, Locality-sensitive hashing, Machine learning, Mahalanobis distance, Metric (mathematics), Ranking, Recommender system, Regression analysis, Sign (mathematics), Similarity measure, Statistical classification, Statistics, Subadditivity, Symmetry.
Artificial intelligence
Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals.
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Bilinear form
In mathematics, more specifically in abstract algebra and linear algebra, a bilinear form on a vector space V is a bilinear map, where K is the field of scalars.
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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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Covariance
In probability theory and statistics, covariance is a measure of the joint variability of two random variables.
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Hash function
A hash function is any function that can be used to map data of arbitrary size to data of a fixed size.
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Identity of indiscernibles
The identity of indiscernibles is an ontological principle that states that there cannot be separate objects or entities that have all their properties in common.
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K-nearest neighbors algorithm
In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression.
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Large margin nearest neighbor
Large margin nearest neighbor (LMNN) classification is a statistical machine learning algorithm for metric learning.
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Latent semantic analysis
Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.
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Locality-sensitive hashing
Locality-sensitive hashing (LSH) reduces the dimensionality of high-dimensional data.
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Machine learning
Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.
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Mahalanobis distance
The Mahalanobis distance is a measure of the distance between a point P and a distribution D, introduced by P. C. Mahalanobis in 1936.
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Metric (mathematics)
In mathematics, a metric or distance function is a function that defines a distance between each pair of elements of a set.
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Ranking
A ranking is a relationship between a set of items such that, for any two items, the first is either 'ranked higher than', 'ranked lower than' or 'ranked equal to' the second.
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Recommender system
A recommender system or a recommendation system (sometimes replacing "system" with a synonym such as platform or engine) is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item.
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Regression analysis
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships among variables.
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Sign (mathematics)
In mathematics, the concept of sign originates from the property of every non-zero real number of being positive or negative.
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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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Statistical classification
In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.
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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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Subadditivity
In mathematics, subadditivity is a property of a function that states, roughly, that evaluating the function for the sum of two elements of the domain always returns something less than or equal to the sum of the function's values at each element.
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Symmetry
Symmetry (from Greek συμμετρία symmetria "agreement in dimensions, due proportion, arrangement") in everyday language refers to a sense of harmonious and beautiful proportion and balance.
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References
[1] https://en.wikipedia.org/wiki/Similarity_learning
