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  2. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Also known as min-max scaling or min-max normalization, rescaling is the simplest method and consists in rescaling the range of features to scale the range in [0, 1] or [−1, 1]. Selecting the target range depends on the nature of the data. The general formula for a min-max of [0, 1] is given as: [3]

  3. Non-negative matrix factorization - Wikipedia

    en.wikipedia.org/wiki/Non-negative_matrix...

    For example, if V is an m × n matrix, W is an m × p matrix, and H is a p × n matrix then p can be significantly less than both m and n. Here is an example based on a text-mining application: Let the input matrix (the matrix to be factored) be V with 10000 rows and 500 columns where words are in rows and documents are in columns. That is, we ...

  4. Softmax function - Wikipedia

    en.wikipedia.org/wiki/Softmax_function

    That is, prior to applying softmax, some vector components could be negative, or greater than one; and might not sum to 1; but after applying softmax, each component will be in the interval (,), and the components will add up to 1, so that they can be interpreted as probabilities. Furthermore, the larger input components will correspond to ...

  5. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    The column space of a matrix is the image or range of the corresponding matrix transformation. Let be a field. The column space of an m × n matrix with components from is a linear subspace of the m-space. The dimension of the column space is called the rank of the matrix and is at most min(m, n). [1]

  6. Iris flower data set - Wikipedia

    en.wikipedia.org/wiki/Iris_flower_data_set

    Scatterplot of the data set. The Iris flower data set or Fisher's Iris data set is a multivariate data set used and made famous by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis. [1]

  7. Successive over-relaxation - Wikipedia

    en.wikipedia.org/wiki/Successive_over-relaxation

    An example is the method of Lewis Fry Richardson, and the methods developed by R. V. Southwell. However, these methods were designed for computation by human calculators , requiring some expertise to ensure convergence to the solution which made them inapplicable for programming on digital computers.

  8. Bland's rule - Wikipedia

    en.wikipedia.org/wiki/Bland's_rule

    Such cycles are avoided by Bland's rule for choosing a column to enter and a column to leave the basis. Bland's rule was developed by Robert G. Bland, now an Emeritus Professor of operations research at Cornell University, while he was a research fellow at the Center for Operations Research and Econometrics in Belgium. [1]

  9. Range tree - Wikipedia

    en.wikipedia.org/wiki/Range_tree

    A 1-dimensional range tree on a set of n points is a binary search tree, which can be constructed in (⁡) time. Range trees in higher dimensions are constructed recursively by constructing a balanced binary search tree on the first coordinate of the points, and then, for each vertex v in this tree, constructing a (d−1)-dimensional range tree on the points contained in the subtree of v.