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  2. CoBoosting - Wikipedia

    en.wikipedia.org/wiki/CoBoosting

    Three equations are defined describing the sum of the distributions for in which the current hypothesis has selected either correct or incorrect label. Note that it is possible for the classifier to abstain from selecting a label for an example, in which the label provided is 0. The two labels are selected to be either -1 or 1.

  3. Multiclass classification - Wikipedia

    en.wikipedia.org/wiki/Multiclass_classification

    The online learning algorithms, on the other hand, incrementally build their models in sequential iterations. In iteration t, an online algorithm receives a sample, x t and predicts its label ŷ t using the current model; the algorithm then receives y t, the true label of x t and updates its model based on the sample-label pair: (x t, y t).

  4. Johnson–Lindenstrauss lemma - Wikipedia

    en.wikipedia.org/wiki/Johnson–Lindenstrauss_lemma

    The lemma has applications in compressed sensing, manifold learning, dimensionality reduction, graph embedding, and natural language processing. Much of the data stored and manipulated on computers, including text and images, can be represented as points in a high-dimensional space (see vector space model for the case of text

  5. Multi-label classification - Wikipedia

    en.wikipedia.org/wiki/Multi-label_classification

    The formulation of multi-label learning was first introduced by Shen et al. in the context of Semantic Scene Classification [1] [2], and later gained popularity across various areas of machine learning. Formally, multi-label classification is the problem of finding a model that maps inputs x to binary vectors y; that is, it assigns a value of 0 ...

  6. Manifold regularization - Wikipedia

    en.wikipedia.org/wiki/Manifold_regularization

    The hypothesis space is an RKHS, meaning that it is associated with a kernel, and so every candidate function has a norm ‖ ‖, which represents the complexity of the candidate function in the hypothesis space. When the algorithm considers a candidate function, it takes its norm into account in order to penalize complex functions.

  7. Three-dimensional space - Wikipedia

    en.wikipedia.org/wiki/Three-dimensional_space

    In geometry, a three-dimensional space (3D space, 3-space or, rarely, tri-dimensional space) is a mathematical space in which three values (coordinates) are required to determine the position of a point. Most commonly, it is the three-dimensional Euclidean space, that is, the Euclidean space of dimension three, which models physical space.

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    mail.aol.com

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  9. Ricci calculus - Wikipedia

    en.wikipedia.org/wiki/Ricci_calculus

    For example, in 3-D Euclidean space and using Cartesian coordinates; the coordinate vector A = (A 1, A 2, A 3) = (A x, A y, A z) shows a direct correspondence between the subscripts 1, 2, 3 and the labels x, y, z. In the expression A i, i is interpreted as an index ranging over the values 1, 2, 3, while the x, y, z subscripts are only labels ...