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ggplot2 is an open-source data visualization package for the statistical programming language R.Created by Hadley Wickham in 2005, ggplot2 is an implementation of Leland Wilkinson's Grammar of Graphics—a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers. ggplot2 can serve as a replacement for the base graphics in R and contains a ...
A Bayes consistent loss function allows us to find the Bayes optimal decision function by directly minimizing the expected risk and without having to explicitly model the probability density functions. For convex margin loss (), it can be shown that () is Bayes consistent if and only if it is differentiable at 0 and ′ <.
H 2 does, but only with a small margin. H 3 separates them with the maximum margin. In machine learning, the margin of a single data point is defined to be the distance from the data point to a decision boundary. Note that there are many distances and decision boundaries that may be appropriate for certain datasets and goals.
The plot shows that the Hinge loss penalizes predictions y < 1, corresponding to the notion of a margin in a support vector machine. In machine learning, the hinge loss is a loss function used for training classifiers. The hinge loss is used for "maximum-margin" classification, most notably for support vector machines (SVMs). [1]
Bibliometrix is a package for the R statistical programming language for quantitative research in scientometrics and bibliometrics. [1]Bibliometrics is the application of quantitative analysis and statistics to publications such as journal articles and their accompanying citation counts.
Image source: The Motley Fool. Apple (NASDAQ: AAPL) Q1 2025 Earnings Call Jan 30, 2025, 5:00 p.m. ET. Contents: Prepared Remarks. Questions and Answers. Call ...
In computer security, an access-control list (ACL) is a list of permissions [a] associated with a system resource (object or facility). An ACL specifies which users or system processes are granted access to resources, as well as what operations are allowed on given resources. [1] Each entry in a typical ACL specifies a subject and an operation.
Large margin nearest neighbor (LMNN) [1] classification is a statistical machine learning algorithm for metric learning. It learns a pseudometric designed for k-nearest neighbor classification. The algorithm is based on semidefinite programming , a sub-class of convex optimization .