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  2. Matrix similarity - Wikipedia

    en.wikipedia.org/wiki/Matrix_similarity

    A transformation A ↦ P −1 AP is called a similarity transformation or conjugation of the matrix A. In the general linear group , similarity is therefore the same as conjugacy , and similar matrices are also called conjugate ; however, in a given subgroup H of the general linear group, the notion of conjugacy may be more restrictive than ...

  3. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    Similarity measures are used to develop recommender systems. It observes a user's perception and liking of multiple items. On recommender systems, the method is using a distance calculation such as Euclidean Distance or Cosine Similarity to generate a similarity matrix with values representing the similarity of any pair of targets. Then, by ...

  4. Jaccard index - Wikipedia

    en.wikipedia.org/wiki/Jaccard_index

    Jaccard distance is commonly used to calculate an n × n matrix for clustering and multidimensional scaling of n sample sets. This distance is a metric on the collection of all finite sets. [ 8 ] [ 9 ] [ 10 ]

  5. BLOSUM - Wikipedia

    en.wikipedia.org/wiki/BLOSUM

    E.g., BLOSUM62 is the matrix built using sequences with less than 62% similarity (sequences with ≥ 62% identity were clustered together). Note: BLOSUM 62 is the default matrix for protein BLAST. Experimentation has shown that the BLOSUM-62 matrix is among the best for detecting most weak protein similarities. [1]

  6. SimRank - Wikipedia

    en.wikipedia.org/wiki/SimRank

    SimRank is a general similarity measure, based on a simple and intuitive graph-theoretic model.SimRank is applicable in any domain with object-to-object relationships, that measures similarity of the structural context in which objects occur, based on their relationships with other objects.

  7. Distance matrix - Wikipedia

    en.wikipedia.org/wiki/Distance_matrix

    They are generally used to calculate the similarity between data points: this is where the distance matrix is an essential element. The use of an effective distance matrix improves the performance of the machine learning model, whether it is for classification tasks or for clustering.

  8. Dot plot (bioinformatics) - Wikipedia

    en.wikipedia.org/wiki/Dot_plot_(bioinformatics)

    One way to visualize the similarity between two protein or nucleic acid sequences is to use a similarity matrix, known as a dot plot. These were introduced by Gibbs and McIntyre in 1970 [1] and are two-dimensional matrices that have the sequences of the proteins being compared along the vertical and horizontal axes.

  9. Trace (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Trace_(linear_algebra)

    If a 2 x 2 real matrix has zero trace, its square is a diagonal matrix. The trace of a 2 × 2 complex matrix is used to classify Möbius transformations. First, the matrix is normalized to make its determinant equal to one. Then, if the square of the trace is 4, the corresponding transformation is parabolic.