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  2. ggplot2 - Wikipedia

    en.wikipedia.org/wiki/Ggplot2

    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 ...

  3. Margin (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Margin_(machine_learning)

    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.

  4. Loss functions for classification - Wikipedia

    en.wikipedia.org/wiki/Loss_functions_for...

    These are called margin-based loss functions. Choosing a margin-based loss function amounts to choosing ϕ {\displaystyle \phi } . Selection of a loss function within this framework impacts the optimal f ϕ ∗ {\displaystyle f_{\phi }^{*}} which minimizes the expected risk, see empirical risk minimization .

  5. Hinge loss - Wikipedia

    en.wikipedia.org/wiki/Hinge_loss

    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]

  6. Apple (AAPL) Q1 2025 Earnings Call Transcript - AOL

    www.aol.com/finance/apple-aapl-q1-2025-earnings...

    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 ...

  7. Large margin nearest neighbor - Wikipedia

    en.wikipedia.org/wiki/Large_Margin_Nearest_Neighbor

    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 .

  8. Aggregate function - Wikipedia

    en.wikipedia.org/wiki/Aggregate_function

    In order to calculate the average and standard deviation from aggregate data, it is necessary to have available for each group: the total of values (Σx i = SUM(x)), the number of values (N=COUNT(x)) and the total of squares of the values (Σx i 2 =SUM(x 2)) of each groups.

  9. Margin (economics) - Wikipedia

    en.wikipedia.org/wiki/Margin_(economics)

    Within economics, margin is a concept used to describe the current level of consumption or production of a good or service. [1] Margin also encompasses various concepts within economics, denoted as marginal concepts , which are used to explain the specific change in the quantity of goods and services produced and consumed.