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  2. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity between two objects. Although no single definition of a similarity exists, usually such measures are in some sense the inverse of distance metrics : they take on large values for similar ...

  3. Simple matching coefficient - Wikipedia

    en.wikipedia.org/wiki/Simple_matching_coefficient

    In this scenario, the similarity between the two baskets as measured by the Jaccard index would be 1/3, but the similarity becomes 0.998 using the SMC. In other contexts, where 0 and 1 carry equivalent information (symmetry), the SMC is a better measure of similarity.

  4. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    Cluster analysis, a fundamental task in data mining and machine learning, involves grouping a set of data points into clusters based on their similarity. k-means clustering is a popular algorithm used for partitioning data into k clusters, where each cluster is represented by its centroid.

  5. Silhouette (clustering) - Wikipedia

    en.wikipedia.org/wiki/Silhouette_(clustering)

    A plot showing silhouette scores from three types of animals from the Zoo dataset as rendered by Orange data mining suite. At the bottom of the plot, silhouette identifies dolphin and porpoise as outliers in the group of mammals. Assume the data have been clustered via any technique, such as k-medoids or k-means, into clusters.

  6. Medoid - Wikipedia

    en.wikipedia.org/wiki/Medoid

    Cosine similarity is a widely used measure to compare the similarity between two pieces of text. It calculates the cosine of the angle between two document vectors in a high-dimensional space. [14] Cosine similarity ranges between -1 and 1, where a value closer to 1 indicates higher similarity, and a value closer to -1 indicates lower similarity.

  7. Similarity learning - Wikipedia

    en.wikipedia.org/wiki/Similarity_learning

    Similarity learning is closely related to distance metric learning.Metric learning is the task of learning a distance function over objects. A metric or distance function has to obey four axioms: non-negativity, identity of indiscernibles, symmetry and subadditivity (or the triangle inequality).

  8. NYT ‘Connections’ Hints and Answers Today, Tuesday ... - AOL

    www.aol.com/nyt-connections-hints-answers-today...

    Get ready for all of today's NYT 'Connections’ hints and answers for #576 on Tuesday, January 7, 2025. Today's NYT Connections puzzle for Tuesday, January 7, 2025The New York Times.

  9. Dice-Sørensen coefficient - Wikipedia

    en.wikipedia.org/wiki/Dice-Sørensen_coefficient

    Other variations include the "similarity coefficient" or "index", such as Dice similarity coefficient (DSC). Common alternate spellings for Sørensen are Sorenson , Soerenson and Sörenson , and all three can also be seen with the –sen ending (the Danish letter ø is phonetically equivalent to the German/Swedish ö, which can be written as oe ...