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  2. DBSCAN - Wikipedia

    en.wikipedia.org/wiki/DBSCAN

    DBSCAN* [6] [7] is a variation that treats border points as noise, and this way achieves a fully deterministic result as well as a more consistent statistical interpretation of density-connected components. The quality of DBSCAN depends on the distance measure used in the function regionQuery(P,ε).

  3. OPTICS algorithm - Wikipedia

    en.wikipedia.org/wiki/OPTICS_algorithm

    The R package "dbscan" includes a C++ implementation of OPTICS (with both traditional dbscan-like and ξ cluster extraction) using a k-d tree for index acceleration for Euclidean distance only. Python implementations of OPTICS are available in the PyClustering library and in scikit-learn. HDBSCAN* is available in the hdbscan library.

  4. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    In Analytica release 4.4, the Smoothing option for PDF results uses KDE, and from expressions it is available via the built-in Pdf function. In C/C++, FIGTree is a library that can be used to compute kernel density estimates using normal kernels. MATLAB interface available. In C++, libagf is a library for variable kernel density estimation.

  5. Local outlier factor - Wikipedia

    en.wikipedia.org/wiki/Local_outlier_factor

    In anomaly detection, the local outlier factor (LOF) is an algorithm proposed by Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng and Jörg Sander in 2000 for finding anomalous data points by measuring the local deviation of a given data point with respect to its neighbours.

  6. Density estimation - Wikipedia

    en.wikipedia.org/wiki/Density_Estimation

    The mean of "glu" in the diabetes cases is 143.1 and the standard deviation is 31.26. The mean of "glu" in the non-diabetes cases is 110.0 and the standard deviation is 24.29. From this we see that, in this data set, diabetes cases are associated with greater levels of "glu". This will be made clearer by plots of the estimated density functions.

  7. Multivariate kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_kernel...

    kde2d.m A Matlab function for bivariate kernel density estimation. libagf A C++ library for multivariate, variable bandwidth kernel density estimation. akde.m A Matlab m-file for multivariate, variable bandwidth kernel density estimation. helit and pyqt_fit.kde Module in the PyQt-Fit package are Python libraries for multivariate kernel density ...

  8. Trump national security adviser: Hamas will never govern Gaza ...

    www.aol.com/news/trump-national-security-adviser...

    President-elect Donald Trump's incoming national security adviser, Mike Waltz, said on Sunday that if Hamas reneges on the Gaza ceasefire-for-hostages deal, the United States will support Israel ...

  9. Mean shift - Wikipedia

    en.wikipedia.org/wiki/Mean_shift

    Mean shift is a non-parametric feature-space mathematical analysis technique for locating the maxima of a density function, a so-called mode-seeking algorithm. [1] Application domains include cluster analysis in computer vision and image processing .