Faster access than browser!
112 relations: Accord.NET, ALGLIB, Apache Mahout, Apache Spark, Association for Computational Linguistics, Astronomy, Autoencoder, Ayasdi, Bell Labs, BFR algorithm, Bilateral filter, Centroid, Centroidal Voronoi tessellation, Cluster analysis, Color quantization, Computer graphics, Computer vision, CrimeStat, Data mining, Data mining in agriculture, David Mount, Determining the number of clusters in a data set, Discrete & Computational Geometry, ELKI, Euclidean distance, Expectation–maximization algorithm, Feature learning, Free and open-source software, Geostatistics, GNU Octave, Head/tail Breaks, Heuristic (computer science), Hugo Steinhaus, IEEE Transactions on Information Theory, Image segmentation, Independent component analysis, Integer lattice, Iris (plant), Iris flower data set, Jenks natural breaks optimization, Journal of the Royal Statistical Society, Julia (programming language), K q-flats, K-d tree, K-means++, K-medians clustering, K-medoids, K-nearest neighbors algorithm, K-SVD, KNIME, ..., Lecture Notes in Computer Science, Linde–Buzo–Gray algorithm, Linear classifier, Lloyd's algorithm, Local optimum, Machine learning, Machine Learning (journal), MapReduce, Market segmentation, MATLAB, Mean, Mean shift, Medoid, Metric (mathematics), Mixture model, MLPACK (C++ library), Named-entity recognition, Nathan Netanyahu, Natural language processing, Nearest centroid classifier, Normal distribution, NP-hardness, OpenCV, Orange (software), Palette (painting), Partition of a set, Principal component analysis, Proceedings of the Royal Society, Proprietary software, PSPP, Pulse-code modulation, R (programming language), Radial basis function, Radial basis function network, RapidMiner, Restricted Boltzmann machine, Rocchio algorithm, Sampling (statistics), SAP HANA, SAS (software), Scikit-learn, SciPy, Self-organizing map, Semi-supervised learning, Signal processing, Silhouette (clustering), Smoothed analysis, SPSS, Stata, Supervised learning, Symposium on Computational Geometry, Taxicab geometry, Torch (machine learning), Triangle inequality, Unsupervised learning, Variance, Vector quantization, Voronoi diagram, Weka (machine learning), Whitening transformation, Wolfram Mathematica, Worst-case complexity. Expand index (62 more) »
Accord.NET
Accord.NET is a framework for scientific computing in.NET.
New!!: K-means clustering and Accord.NET · See more »
ALGLIB
ALGLIB is a cross-platform open source numerical analysis and data processing library.
New!!: K-means clustering and ALGLIB · See more »
Apache Mahout
Apache Mahout is a project of the Apache Software Foundation to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily in the areas of collaborative filtering, clustering and classification.
New!!: K-means clustering and Apache Mahout · See more »
Apache Spark
Apache Spark is an open-source cluster-computing framework.
New!!: K-means clustering and Apache Spark · See more »
Association for Computational Linguistics
The Association for Computational Linguistics (ACL) is the international scientific and professional society for people working on problems involving natural language and computation.
New!!: K-means clustering and Association for Computational Linguistics · See more »
Astronomy
Astronomy (from ἀστρονομία) is a natural science that studies celestial objects and phenomena.
New!!: K-means clustering and Astronomy · See more »
Autoencoder
An autoencoder is a type of artificial neural network used to learn efficient data codings in an unsupervised manner.
New!!: K-means clustering and Autoencoder · See more »
Ayasdi
Ayasdi is a machine intelligence software company that offers a software platform and applications to organizations looking to analyze and build predictive models using big data or highly dimensional data sets.
New!!: K-means clustering and Ayasdi · See more »
Bell Labs
Nokia Bell Labs (formerly named AT&T Bell Laboratories, Bell Telephone Laboratories and Bell Labs) is an American research and scientific development company, owned by Finnish company Nokia.
New!!: K-means clustering and Bell Labs · See more »
BFR algorithm
The BFR algorithm, named after its inventors Bradley, Fayyad and Reina, is a variant of k-means algorithm that is designed to cluster data in a high-dimensional Euclidean space.
New!!: K-means clustering and BFR algorithm · See more »
Bilateral filter
A bilateral filter is a non-linear, edge-preserving, and noise-reducing smoothing filter for images.
New!!: K-means clustering and Bilateral filter · See more »
Centroid
In mathematics and physics, the centroid or geometric center of a plane figure is the arithmetic mean position of all the points in the shape.
New!!: K-means clustering and Centroid · See more »
Centroidal Voronoi tessellation
In geometry, a centroidal Voronoi tessellation (CVT) is a special type of Voronoi tessellation or Voronoi diagram.
New!!: K-means clustering and Centroidal Voronoi tessellation · See more »
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).
New!!: K-means clustering and Cluster analysis · See more »
Color quantization
In computer graphics, color quantization or color image quantization is a process that reduces the number of distinct colors used in an image, usually with the intention that the new image should be as visually similar as possible to the original image.
New!!: K-means clustering and Color quantization · See more »
Computer graphics
Computer graphics are pictures and films created using computers.
New!!: K-means clustering and Computer graphics · See more »
Computer vision
Computer vision is a field that deals with how computers can be made for gaining high-level understanding from digital images or videos.
New!!: K-means clustering and Computer vision · See more »
CrimeStat
CrimeStat is a crime mapping software program.
New!!: K-means clustering and CrimeStat · See more »
Data mining
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
New!!: K-means clustering and Data mining · See more »
Data mining in agriculture
Data mining in agriculture is a very recent research topic.
New!!: K-means clustering and Data mining in agriculture · See more »
David Mount
David Mount is a professor at University of Maryland Department of Computer Science (College Park Campus) whose research is in computational geometry.
New!!: K-means clustering and David Mount · See more »
Determining the number of clusters in a data set
Determining the number of clusters in a data set, a quantity often labelled k as in the ''k''-means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem.
New!!: K-means clustering and Determining the number of clusters in a data set · See more »
Discrete & Computational Geometry
Discrete & Computational Geometry is a peer-reviewed mathematics journal published quarterly by Springer.
New!!: K-means clustering and Discrete & Computational Geometry · See more »
ELKI
ELKI (for Environment for DeveLoping KDD-Applications Supported by Index-Structures) is a knowledge discovery in databases (KDD, "data mining") software framework developed for use in research and teaching originally at the database systems research unit of Professor Hans-Peter Kriegel at the Ludwig Maximilian University of Munich, Germany.
New!!: K-means clustering and ELKI · See more »
Euclidean distance
In mathematics, the Euclidean distance or Euclidean metric is the "ordinary" straight-line distance between two points in Euclidean space.
New!!: K-means clustering and Euclidean distance · See more »
Expectation–maximization algorithm
In statistics, an expectation–maximization (EM) algorithm is an iterative method to find maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables.
New!!: K-means clustering and Expectation–maximization algorithm · See more »
Feature learning
In machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data.
New!!: K-means clustering and Feature learning · See more »
Free and open-source software
Free and open-source software (FOSS) is software that can be classified as both free software and open-source software.
New!!: K-means clustering and Free and open-source software · See more »
Geostatistics
Geostatistics is a branch of statistics focusing on spatial or spatiotemporal datasets.
New!!: K-means clustering and Geostatistics · See more »
GNU Octave
GNU Octave is software featuring a high-level programming language, primarily intended for numerical computations.
New!!: K-means clustering and GNU Octave · See more »
Head/tail Breaks
Head/tail breaks is a clustering algorithm scheme for data with a heavy-tailed distribution such as power laws and lognormal distributions.
New!!: K-means clustering and Head/tail Breaks · See more »
Heuristic (computer science)
In computer science, artificial intelligence, and mathematical optimization, a heuristic (from Greek εὑρίσκω "I find, discover") is a technique designed for solving a problem more quickly when classic methods are too slow, or for finding an approximate solution when classic methods fail to find any exact solution.
New!!: K-means clustering and Heuristic (computer science) · See more »
Hugo Steinhaus
Władysław Hugo Dionizy Steinhaus (January 14, 1887 – February 25, 1972) was a Jewish-Polish mathematician and educator.
New!!: K-means clustering and Hugo Steinhaus · See more »
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory is a monthly peer-reviewed scientific journal published by the IEEE Information Theory Society.
New!!: K-means clustering and IEEE Transactions on Information Theory · See more »
Image segmentation
In computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as super-pixels).
New!!: K-means clustering and Image segmentation · See more »
Independent component analysis
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents.
New!!: K-means clustering and Independent component analysis · See more »
Integer lattice
In mathematics, the n-dimensional integer lattice (or cubic lattice), denoted Zn, is the lattice in the Euclidean space Rn whose lattice points are ''n''-tuples of integers.
New!!: K-means clustering and Integer lattice · See more »
Iris (plant)
Iris is a genus of 260–300 species of flowering plants with showy flowers.
New!!: K-means clustering and Iris (plant) · See more »
Iris flower data set
The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis.
New!!: K-means clustering and Iris flower data set · See more »
Jenks natural breaks optimization
The Jenks optimization method, also called the Jenks natural breaks classification method, is a data clustering method designed to determine the best arrangement of values into different classes.
New!!: K-means clustering and Jenks natural breaks optimization · See more »
Journal of the Royal Statistical Society
The Journal of the Royal Statistical Society is a peer-reviewed scientific journal of statistics.
New!!: K-means clustering and Journal of the Royal Statistical Society · See more »
Julia (programming language)
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science, without the typical need of separate compilation to be fast, while also being effective for general-purpose programming, web use or as a specification language.
New!!: K-means clustering and Julia (programming language) · See more »
K q-flats
In data mining and machine learning, k q-flats algorithm is an iterative method which aims to partition m observations into k clusters where each cluster is close to a q-flat, where q is a given integer.
New!!: K-means clustering and K q-flats · See more »
K-d tree
In computer science, a k-d tree (short for k-dimensional tree) is a space-partitioning data structure for organizing points in a k-dimensional space.
New!!: K-means clustering and K-d tree · See more »
K-means++
In data mining, k-means++ is an algorithm for choosing the initial values (or "seeds") for the ''k''-means clustering algorithm.
New!!: K-means clustering and K-means++ · See more »
K-medians clustering
In statistics and data mining, k-medians clustering is a cluster analysis algorithm.
New!!: K-means clustering and K-medians clustering · See more »
K-medoids
The -medoids algorithm is a clustering algorithm related to the k-means algorithm and the medoidshift algorithm.
New!!: K-means clustering and K-medoids · See more »
K-nearest neighbors algorithm
In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression.
New!!: K-means clustering and K-nearest neighbors algorithm · See more »
K-SVD
In applied mathematics, K-SVD is a dictionary learning algorithm for creating a dictionary for sparse representations, via a singular value decomposition approach.
New!!: K-means clustering and K-SVD · See more »
KNIME
KNIME, the Konstanz Information Miner, is a free and open-source data analytics, reporting and integration platform.
New!!: K-means clustering and KNIME · See more »
Lecture Notes in Computer Science
Springer Lecture Notes in Computer Science (LNCS) is a series of computer science books published by Springer Science+Business Media (formerly Springer-Verlag) since 1973.
New!!: K-means clustering and Lecture Notes in Computer Science · See more »
Linde–Buzo–Gray algorithm
The Linde–Buzo–Gray algorithm (introduced by Yoseph Linde, Andrés Buzo and Robert M. Gray in 1980) is a vector quantization algorithm to derive a good codebook.
New!!: K-means clustering and Linde–Buzo–Gray algorithm · See more »
Linear classifier
In the field of machine learning, the goal of statistical classification is to use an object's characteristics to identify which class (or group) it belongs to.
New!!: K-means clustering and Linear classifier · See more »
Lloyd's algorithm
In computer science and electrical engineering, Lloyd's algorithm, also known as Voronoi iteration or relaxation, is an algorithm named after Stuart P. Lloyd for finding evenly spaced sets of points in subsets of Euclidean spaces and partitions of these subsets into well-shaped and uniformly sized convex cells.
New!!: K-means clustering and Lloyd's algorithm · See more »
Local optimum
In applied mathematics and computer science, a local optimum of an optimization problem is a solution that is optimal (either maximal or minimal) within a neighboring set of candidate solutions.
New!!: K-means clustering and Local optimum · See more »
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.
New!!: K-means clustering and Machine learning · See more »
Machine Learning (journal)
Machine Learning is a peer-reviewed scientific journal, published since 1986.
New!!: K-means clustering and Machine Learning (journal) · See more »
MapReduce
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a cluster.
New!!: K-means clustering and MapReduce · See more »
Market segmentation
Market segmentation is the process of dividing a broad consumer or business market, normally consisting of existing and potential customers, into sub-groups of consumers (known as segments) based on some type of shared characteristics.
New!!: K-means clustering and Market segmentation · See more »
MATLAB
MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and proprietary programming language developed by MathWorks.
New!!: K-means clustering and MATLAB · See more »
Mean
In mathematics, mean has several different definitions depending on the context.
New!!: K-means clustering and Mean · See more »
Mean shift
Mean shift is a non-parametric feature-space analysis technique for locating the maxima of a density function, a so-called mode-seeking algorithm.
New!!: K-means clustering and Mean shift · See more »
Medoid
Medoids are representative objects of a data set or a cluster with a data set whose average dissimilarity to all the objects in the cluster is minimal.
New!!: K-means clustering and Medoid · See more »
Metric (mathematics)
In mathematics, a metric or distance function is a function that defines a distance between each pair of elements of a set.
New!!: K-means clustering and Metric (mathematics) · See more »
Mixture model
In statistics, a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs.
New!!: K-means clustering and Mixture model · See more »
MLPACK (C++ library)
mlpack is a machine learning software library for C++, built on top of the Armadillo library.
New!!: K-means clustering and MLPACK (C++ library) · See more »
Named-entity recognition
Named-entity recognition (NER) (also known as entity identification, entity chunking and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities in text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
New!!: K-means clustering and Named-entity recognition · See more »
Nathan Netanyahu
Nathan S. Netanyahu (נָתָן נְתַנְיָהוּ; born 28 November 1951) is an Israeli computer scientist, a professor of computer science at Bar-Ilan University.
New!!: K-means clustering and Nathan Netanyahu · See more »
Natural language processing
Natural language processing (NLP) is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.
New!!: K-means clustering and Natural language processing · See more »
Nearest centroid classifier
In machine learning, a nearest centroid classifier or nearest prototype classifier is a classification model that assigns to observations the label of the class of training samples whose mean (centroid) is closest to the observation.
New!!: K-means clustering and Nearest centroid classifier · See more »
Normal distribution
In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.
New!!: K-means clustering and Normal distribution · See more »
NP-hardness
NP-hardness (''n''on-deterministic ''p''olynomial-time hardness), in computational complexity theory, is the defining property of a class of problems that are, informally, "at least as hard as the hardest problems in NP".
New!!: K-means clustering and NP-hardness · See more »
OpenCV
OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision.
New!!: K-means clustering and OpenCV · See more »
Orange (software)
Orange is an open-source data visualization, machine learning and data mining toolkit.
New!!: K-means clustering and Orange (software) · See more »
Palette (painting)
A palette, in the original sense of the word, is a rigid, flat surface on which a painter arranges and mixes paints.
New!!: K-means clustering and Palette (painting) · See more »
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.
New!!: K-means clustering and Partition of a set · See more »
Principal component analysis
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.
New!!: K-means clustering and Principal component analysis · See more »
Proceedings of the Royal Society
Proceedings of the Royal Society is the parent title of two scientific journals published by the Royal Society.
New!!: K-means clustering and Proceedings of the Royal Society · See more »
Proprietary software
Proprietary software is non-free computer software for which the software's publisher or another person retains intellectual property rights—usually copyright of the source code, but sometimes patent rights.
New!!: K-means clustering and Proprietary software · See more »
PSPP
PSPP is a free software application for analysis of sampled data, intended as a free alternative for IBM SPSS Statistics.
New!!: K-means clustering and PSPP · See more »
Pulse-code modulation
Pulse-code modulation (PCM) is a method used to digitally represent sampled analog signals.
New!!: K-means clustering and Pulse-code modulation · See more »
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.
New!!: K-means clustering and R (programming language) · See more »
Radial basis function
A radial basis function (RBF) is a real-valued function whose value depends only on the distance from the origin, so that \phi\left(\mathbf\right).
New!!: K-means clustering and Radial basis function · See more »
Radial basis function network
In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions.
New!!: K-means clustering and Radial basis function network · See more »
RapidMiner
RapidMiner is a data science software platform developed by the company of the same name that provides an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics.
New!!: K-means clustering and RapidMiner · See more »
Restricted Boltzmann machine
A restricted Boltzmann machine (RBM) is a generative stochastic artificial neural network that can learn a probability distribution over its set of inputs.
New!!: K-means clustering and Restricted Boltzmann machine · See more »
Rocchio algorithm
The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System which was developed 1960-1964.
New!!: K-means clustering and Rocchio algorithm · See more »
Sampling (statistics)
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.
New!!: K-means clustering and Sampling (statistics) · See more »
SAP HANA
SAP HANA is an in-memory, column-oriented, relational database management system developed and marketed by SAP SE.
New!!: K-means clustering and SAP HANA · See more »
SAS (software)
SAS (previously "Statistical Analysis System") is a software suite developed by SAS Institute for advanced analytics, multivariate analyses, business intelligence, data management, and predictive analytics.
New!!: K-means clustering and SAS (software) · See more »
Scikit-learn
Scikit-learn (formerly scikits.learn) is a free software machine learning library for the Python programming language.
New!!: K-means clustering and Scikit-learn · See more »
SciPy
SciPy (pronounced /ˈsaɪpaɪ'/ "Sigh Pie") is a free and open-source Python library used for scientific computing and technical computing.
New!!: K-means clustering and SciPy · See more »
Self-organizing map
A self-organizing map (SOM) or self-organizing feature map (SOFM) is a type of artificial neural network (ANN) that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional), discretized representation of the input space of the training samples, called a map, and is therefore a method to do dimensionality reduction.
New!!: K-means clustering and Self-organizing map · See more »
Semi-supervised learning
Semi-supervised learning is a class of supervised learning tasks and techniques that also make use of unlabeled data for training – typically a small amount of labeled data with a large amount of unlabeled data.
New!!: K-means clustering and Semi-supervised learning · See more »
Signal processing
Signal processing concerns the analysis, synthesis, and modification of signals, which are broadly defined as functions conveying "information about the behavior or attributes of some phenomenon", such as sound, images, and biological measurements.
New!!: K-means clustering and Signal processing · See more »
Silhouette (clustering)
Silhouette refers to a method of interpretation and validation of consistency within clusters of data.
New!!: K-means clustering and Silhouette (clustering) · See more »
Smoothed analysis
Smoothed analysis is a way of measuring the complexity of an algorithm.
New!!: K-means clustering and Smoothed analysis · See more »
SPSS
SPSS Statistics is a software package used for interactive, or batched, statistical analysis.
New!!: K-means clustering and SPSS · See more »
Stata
Stata is a general-purpose statistical software package created in 1985 by StataCorp.
New!!: K-means clustering and Stata · See more »
Supervised learning
Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs.
New!!: K-means clustering and Supervised learning · See more »
Symposium on Computational Geometry
The Annual Symposium on Computational Geometry (SoCG) is an academic conference in computational geometry.
New!!: K-means clustering and Symposium on Computational Geometry · See more »
Taxicab geometry
A taxicab geometry is a form of geometry in which the usual distance function or metric of Euclidean geometry is replaced by a new metric in which the distance between two points is the sum of the absolute differences of their Cartesian coordinates.
New!!: K-means clustering and Taxicab geometry · See more »
Torch (machine learning)
Torch is an open source machine learning library, a scientific computing framework, and a script language based on the Lua programming language.
New!!: K-means clustering and Torch (machine learning) · See more »
Triangle inequality
In mathematics, the triangle inequality states that for any triangle, the sum of the lengths of any two sides must be greater than or equal to the length of the remaining side.
New!!: K-means clustering and Triangle inequality · See more »
Unsupervised learning
Unsupervised machine learning is the machine learning task of inferring a function that describes the structure of "unlabeled" data (i.e. data that has not been classified or categorized).
New!!: K-means clustering and Unsupervised learning · See more »
Variance
In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its mean.
New!!: K-means clustering and Variance · See more »
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.
New!!: K-means clustering and Vector quantization · See more »
Voronoi diagram
In mathematics, a Voronoi diagram is a partitioning of a plane into regions based on distance to points in a specific subset of the plane.
New!!: K-means clustering and Voronoi diagram · See more »
Weka (machine learning)
Waikato Environment for Knowledge Analysis (Weka) is a suite of machine learning software written in Java, developed at the University of Waikato, New Zealand.
New!!: K-means clustering and Weka (machine learning) · See more »
Whitening transformation
A whitening transformation or sphering transformation is a linear transformation that transforms a vector of random variables with a known covariance matrix into a set of new variables whose covariance is the identity matrix, meaning that they are uncorrelated and each have variance 1.
New!!: K-means clustering and Whitening transformation · See more »
Wolfram Mathematica
Wolfram Mathematica (usually termed Mathematica) is a modern technical computing system spanning most areas of technical computing — including neural networks, machine learning, image processing, geometry, data science, visualizations, and others.
New!!: K-means clustering and Wolfram Mathematica · See more »
Worst-case complexity
In computer science, the worst-case complexity (usually denoted in asymptotic notation) measures the resources (e.g. running time, memory) an algorithm requires in the worst-case.
New!!: K-means clustering and Worst-case complexity · See more »
Redirects here:
Algorithms for k-means clustering, Cluster seeking, K means, K-Means, K-Means Algorithm, K-Means algorithm, K-means, K-means Clustering, K-means algorithm, K-means clustering algorithm, Kmeans.
References
[1] https://en.wikipedia.org/wiki/K-means_clustering
