Grund Error
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publishersPoliciesContact Project Euclidfor Researchers Manage my accountAccessing Project EuclidAccess levelsPay-per-view and print-on-demandfor Librarians Manage my accountAccess levelsCollections, titles, and orderingLibrarian toolsfor Publishers Manage my accountYour disk i/o error skype publication in Project EuclidDiscovery service partnersPublisher tools The Annals of StatisticsInfoCurrent issueAll issuesSearch ← Previous articleTOCNext article → Ann. Statist. Volume 23, Number 6 (1995), 2264-2284.On the minimisation of $L\sp p$ error in mode estimationBirgit Grund and Peter Hall More by Birgit GrundSearch this author in:Google ScholarProject Euclid More by Peter HallSearch this author in:Google ScholarProject Euclid Full-text: Open access PDF File (327 KB) AbstractArticle info and citationFirst pageReferencesAbstract We show that, for $L^p$ convergence of the mode of a nonparametric density estimator to the mode of an unknown probability density, finiteness of the pth moment of the underlying distribution is both necessary and sufficient. The basic requirement of existence of finite variance has been overlooked by statisti
reliable sources. Unsourced material may be challenged and removed. (June 2015) (Learn how and when to remove this template message) Ground truth is a term used in various fields to refer to information provided by direct observation as skype i/o error windows 10 opposed to information provided by inference. Contents 1 Statistics and machine learning 2 Meteorology 2.1 ground truth synonym Errors of commission 2.2 Errors of omission 3 Geographical Information Systems 4 Military usage 5 Etymology 6 References 7 External links
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Statistics and machine learning[edit] In machine learning, the term "ground truth" refers to the accuracy of the training set's classification for supervised learning techniques. This is used in statistical models to prove or disprove research hypotheses. https://projecteuclid.org/euclid.aos/1034713656 The term "ground truthing" refers to the process of gathering the proper objective (provable) data for this test. Compare with gold standard. Bayesian spam filtering is a common example of supervised learning. In this system, the algorithm is manually taught the differences between spam and non-spam. This depends on the ground truth of the messages used to train the algorithm – inaccuracies in the ground truth will correlate to inaccuracies in https://en.wikipedia.org/wiki/Ground_truth the resulting spam/non-spam verdicts. Meteorology[edit] In remote sensing, "ground truth" refers to information collected on location. Ground truth allows image data to be related to real features and materials on the ground. The collection of ground-truth data enables calibration of remote-sensing data, and aids in the interpretation and analysis of what is being sensed. Examples include cartography, meteorology, analysis of aerial photographs, satellite imagery and other techniques in which data are gathered at a distance. More specifically, ground truth may refer to a process in which a pixel on a satellite image is compared to what is there in reality (at the present time) in order to verify the contents of the pixel on the image. In the case of a classified image, it allows supervised classification to help determine the accuracy of the classification performed by the remote sensing software and therefore minimize errors in the classification such as errors of commission and errors of omission. Ground truth is usually done on site, performing surface observations and measurements of various properties of the features of the ground resolution cells that are being studied on the remotely sensed digital image. It also involves taking geographic coordinates of the ground resolution cell with GPS technology and comparing those with the coordinates of the pi
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