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  2. Kemeny–Young method - Wikipedia

    en.wikipedia.org/wiki/Kemeny–Young_method

    Kemeny-Young Optimal Rank Aggregation in PythonTutorial that uses a simple formulation as integer program and is adaptable to other languages with bindings to lpsolve. QuickVote — A website that calculates Kemeny–Young results, and gives further explanation and examples of the concept. It also calculates the winner according to ...

  3. Bootstrap aggregating - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_aggregating

    Bootstrap aggregating, also called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and accuracy of ML classification and regression algorithms.

  4. Aggregate pattern - Wikipedia

    en.wikipedia.org/wiki/Aggregate_pattern

    In Design Patterns, an aggregate is not a design pattern but rather refers to an object such as a list, vector, or generator which provides an interface for creating iterators. The following example code is in Python.

  5. Class diagram - Wikipedia

    en.wikipedia.org/wiki/Class_diagram

    Aggregation is a variant of the "has a" association relationship; aggregation is more specific than association. It is an association that represents a part-whole or part-of relationship. As shown in the image, a Professor 'has a' class to teach. As a type of association, an aggregation can be named and have the same adornments that an ...

  6. Data aggregation - Wikipedia

    en.wikipedia.org/wiki/Data_aggregation

    The information is packaged into aggregate reports and then sold to businesses, as well as to local, state, and government agencies. This information can also be useful for marketing purposes. In the United States, many data brokers' activities fall under the Fair Credit Reporting Act (FCRA) which regulates consumer reporting agencies .

  7. Ward's method - Wikipedia

    en.wikipedia.org/wiki/Ward's_method

    Ward's minimum variance method can be defined and implemented recursively by a Lance–Williams algorithm. The Lance–Williams algorithms are an infinite family of agglomerative hierarchical clustering algorithms which are represented by a recursive formula for updating cluster distances at each step (each time a pair of clusters is merged).

  8. Aggregate function - Wikipedia

    en.wikipedia.org/wiki/Aggregate_function

    In other cases the aggregate cannot be computed without analyzing the entire set at once, though in some cases approximations can be distributed; examples include DISTINCT COUNT (Count-distinct problem), MEDIAN, and MODE. Such functions are called decomposable aggregation functions [4] or decomposable aggregate functions.

  9. Object composition - Wikipedia

    en.wikipedia.org/wiki/Object_composition

    The relationship between the aggregate and its components is a weak "has-a" relationship: The components may be part of several aggregates, may be accessed through other objects without going through the aggregate, and may outlive the aggregate object. [4] The state of the component object still forms part of the aggregate object. [citation needed]