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  2. Joint probability distribution - Wikipedia

    en.wikipedia.org/wiki/Joint_probability_distribution

    Moreover, the final row and the final column give the marginal probability distribution for A and the marginal probability distribution for B respectively. For example, for A the first of these cells gives the sum of the probabilities for A being red, regardless of which possibility for B in the column above the cell occurs, as ⁠ 2 / 3 ⁠.

  3. Marginal distribution - Wikipedia

    en.wikipedia.org/wiki/Marginal_distribution

    For example, suppose P(L = red) = 0.2, P(L = yellow) = 0.1, and P(L = green) = 0.7. Multiplying each column in the conditional distribution by the probability of that column occurring results in the joint probability distribution of H and L, given in the central 2×3 block of entries. (Note that the cells in this 2×3 block add up to 1).

  4. Single-linkage clustering - Wikipedia

    en.wikipedia.org/wiki/Single-linkage_clustering

    Merge clusters () and () into a single cluster to form the next clustering . Set the level of this clustering to L ( m ) = d [ ( r ) , ( s ) ] {\displaystyle L(m)=d[(r),(s)]} Update the proximity matrix, D {\displaystyle D} , by deleting the rows and columns corresponding to clusters ( r ) {\displaystyle (r)} and ( s ) {\displaystyle (s)} and ...

  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. Join-based tree algorithms - Wikipedia

    en.wikipedia.org/wiki/Join-based_tree_algorithms

    Under this framework, the join operation captures all balancing criteria of different balancing schemes, and all other functions join have generic implementation across different balancing schemes. The join-based algorithms can be applied to at least four balancing schemes: AVL trees, red–black trees, weight-balanced trees and treaps.

  7. Main effect - Wikipedia

    en.wikipedia.org/wiki/Main_effect

    The expected value for the mean of the responses in column i is + while the expected value for the mean of the responses in row j is + where i corresponds to the level of factor in factor A and j corresponds to the level of factor in factor B. and are main effects.

  8. dBase - Wikipedia

    en.wikipedia.org/wiki/DBase

    Can convert dBASE data from .dbf files to CSV, HTML, Microsoft Excel 2003 and below, Microsoft Excel 2008 and above, or XML. dbDOS PRO 4.0 May 6, 2015 dBase, LLC Unveils New Version of dbDOS PRO 4! [33] dbDOS PRO 4, the latest version of the best-selling solution for supporting MS-DOS based applications on Windows Vista and above operating systems.

  9. Kendall rank correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Kendall_rank_correlation...

    The second algorithm [20] is based on Hermite series estimators and utilizes an alternative estimator for the exact Kendall rank correlation coefficient i.e. for the probability of concordance minus the probability of discordance of pairs of bivariate observations. This alternative estimator also serves as an approximation to the standard ...