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  2. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.

  3. Multivariate kernel density estimation - Wikipedia

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

    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. It can be viewed as a generalisation of histogram density estimation with improved statistical properties.

  4. Density estimation - Wikipedia

    en.wikipedia.org/wiki/Density_Estimation

    Density estimation is also frequently used in anomaly detection or novelty detection: [8] if an observation lies in a very low-density region, it is likely to be an anomaly or a novelty. In hydrology the histogram and estimated density function of rainfall and river discharge data, analysed with a probability distribution , are used to gain ...

  5. Predictive methods for surgery duration - Wikipedia

    en.wikipedia.org/wiki/Predictive_methods_for...

    Occasionally, predictive methods are developed that are valid for a general SD distribution, or more advanced techniques, like Kernel Density Estimation (KDE), are used instead of the traditional methods (like distribution-fitting or regression-oriented methods). There is broad consensus that the three-parameter lognormal describes best most SD ...

  6. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  7. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK. There is also a procedural "pylab" interface based on a state machine (like OpenGL ...

  8. Residents in rural Texas are suing their noisy neighbor: a ...

    www.aol.com/residents-rural-texas-suing-noisy...

    October 11, 2024 at 1:08 PM. Residents in Texas have filed a lawsuit against a bitcoin mine, alleging it's too loud. Stephen Lam/Getty Images. Residents near Granbury, Texas, want an 'intolerably ...

  9. LabPlot - Wikipedia

    en.wikipedia.org/wiki/LabPlot

    LabPlot is a free and open-source, cross-platform computer program for interactive scientific plotting, curve fitting, nonlinear regression, data processing and data analysis. LabPlot is available, under the GPL-2.0-or-later license, for Windows, macOS, Linux, FreeBSD and Haiku operating systems. It has a graphical user interface, a command ...