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  2. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Set-Membership constraints: The values for a column come from a set of discrete values or codes. For example, a person's sex may be Female, Male or Non-Binary. Foreign-key constraints: This is the more general case of set membership. The set of values in a column is defined in a column of another table that contains unique values.

  3. Entity–attribute–value model - Wikipedia

    en.wikipedia.org/wiki/Entity–attribute–value...

    An entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforeseeable using a fixed design.

  4. Data-driven programming - Wikipedia

    en.wikipedia.org/wiki/Data-driven_programming

    It could also record how many warnings are logged per day. Alternatively, one can process streams of delimiter-separated values, processing each line or aggregated lines, such as the sum or max. In email, a language like procmail can specify conditions to match on some emails, and what actions to take (deliver, bounce, discard, forward, etc.).

  5. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    What is the sorted order of a set S of data cases according to their value of attribute A? - Order the cars by weight. - Rank the cereals by calories. 6 Determine Range: Given a set of data cases and an attribute of interest, find the span of values within the set. What is the range of values of attribute A in a set S of data cases?

  6. Heteroskedasticity-consistent standard errors - Wikipedia

    en.wikipedia.org/wiki/Heteroskedasticity...

    where is a vector of observations , and denotes the matrix of stacked values observed in the data. If the sample errors have equal variance σ 2 {\displaystyle \sigma ^{2}} and are uncorrelated , then the least-squares estimate of β {\displaystyle {\boldsymbol {\beta }}} is BLUE (best linear unbiased estimator), and its variance is estimated with

  7. Permutation matrix - Wikipedia

    en.wikipedia.org/wiki/Permutation_matrix

    Multiplying a matrix M by either or on either the left or the right will permute either the rows or columns of M by either π or π −1.The details are a bit tricky. To begin with, when we permute the entries of a vector (, …,) by some permutation π, we move the entry of the input vector into the () slot of the output vector.

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  9. Lift (data mining) - Wikipedia

    en.wikipedia.org/wiki/Lift_(data_mining)

    where the antecedent is the input variable that we can control, and the consequent is the variable we are trying to predict. Real mining problems would typically have more complex antecedents, but usually focus on single-value consequents. Most mining algorithms would determine the following rules (targeting models): Rule 1: A implies 0