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  2. Matrix similarity - Wikipedia

    en.wikipedia.org/wiki/Matrix_similarity

    In linear algebra, two n-by-n matrices A and B are called similar if there exists an invertible n-by-n matrix P such that =. Similar matrices represent the same linear map under two (possibly) different bases, with P being the change-of-basis matrix. [1] [2]

  3. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    Similarities among 162 Relevant Nuclear Profile are tested using the Jaccard Similarity measure (see figure with heatmap). The Jaccard similarity of the nuclear profile ranges from 0 to 1, with 0 indicating no similarity between the two sets and 1 indicating perfect similarity with the aim of clustering the most similar nuclear profile.

  4. Similarity (geometry) - Wikipedia

    en.wikipedia.org/wiki/Similarity_(geometry)

    If two angles of a triangle have measures equal to the measures of two angles of another triangle, then the triangles are similar. Corresponding sides of similar polygons are in proportion, and corresponding angles of similar polygons have the same measure. Two congruent shapes are similar, with a scale factor of 1. However, some school ...

  5. Simple matching coefficient - Wikipedia

    en.wikipedia.org/wiki/Simple_matching_coefficient

    The main difference is that the SMC has the term in its numerator and denominator, whereas the Jaccard index does not. Thus, the SMC counts both mutual presences (when an attribute is present in both sets) and mutual absence (when an attribute is absent in both sets) as matches and compares it to the total number of attributes in the universe ...

  6. Cosine similarity - Wikipedia

    en.wikipedia.org/wiki/Cosine_similarity

    Cosine similarity then gives a useful measure of how similar two documents are likely to be, in terms of their subject matter, and independently of the length of the documents. [1] The technique is also used to measure cohesion within clusters in the field of data mining. [2]

  7. Isometry - Wikipedia

    en.wikipedia.org/wiki/Isometry

    Definition: [7] The midpoint of two elements x and y in a vector space is the vector ⁠ 1 / 2 ⁠ (x + y). Theorem [ 7 ] [ 8 ] — Let A : X → Y be a surjective isometry between normed spaces that maps 0 to 0 ( Stefan Banach called such maps rotations ) where note that A is not assumed to be a linear isometry.

  8. Matrix equivalence - Wikipedia

    en.wikipedia.org/wiki/Matrix_equivalence

    In linear algebra, two rectangular m-by-n matrices A and B are called equivalent if = for some invertible n-by-n matrix P and some invertible m-by-m matrix Q.Equivalent matrices represent the same linear transformation V → W under two different choices of a pair of bases of V and W, with P and Q being the change of basis matrices in V and W respectively.

  9. Pairing - Wikipedia

    en.wikipedia.org/wiki/Pairing

    A pairing can also be considered as an R-linear map: ⁡ (,), which matches the first definition by setting ():= (,). A pairing is called perfect if the above map Φ {\displaystyle \Phi } is an isomorphism of R -modules and the other evaluation map Φ ′ : N → Hom R ⁡ ( M , L ) {\displaystyle \Phi '\colon N\to \operatorname {Hom} _{R}(M,L ...