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  2. Cosine similarity - Wikipedia

    en.wikipedia.org/wiki/Cosine_similarity

    Cosine similarity is the cosine of the angle between the vectors; that is, it is the dot product of the vectors divided by the product of their lengths. It follows that the cosine similarity does not depend on the magnitudes of the vectors, but only on their angle. The cosine similarity always belongs to the interval [,].

  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. List of trigonometric identities - Wikipedia

    en.wikipedia.org/wiki/List_of_trigonometric...

    A formula for computing the trigonometric identities for the one-third angle exists, but it requires finding the zeroes of the cubic equation 4x 3 − 3x + d = 0, where is the value of the cosine function at the one-third angle and d is the known value of the cosine function at the full angle.

  5. Similarity (network science) - Wikipedia

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

    Salton proposed that we regard the i-th and j-th rows/columns of the adjacency matrix as two vectors and use the cosine of the angle between them as a similarity measure. The cosine similarity of i and j is the number of common neighbors divided by the geometric mean of their degrees. [4] Its value lies in the range from 0 to 1.

  6. Simple matching coefficient - Wikipedia

    en.wikipedia.org/wiki/Simple_matching_coefficient

    For example, consider a supermarket with 1000 products and two customers. The basket of the first customer contains salt and pepper and the basket of the second contains salt and sugar. 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.

  7. Pythagorean trigonometric identity - Wikipedia

    en.wikipedia.org/wiki/Pythagorean_trigonometric...

    A calculation confirms that z(0) = 1, and z is a constant so z = 1 for all x, so the Pythagorean identity is established. A similar proof can be completed using power series as above to establish that the sine has as its derivative the cosine, and the cosine has as its derivative the negative sine.

  8. Proofs of trigonometric identities - Wikipedia

    en.wikipedia.org/wiki/Proofs_of_trigonometric...

    For example, the sine of angle θ is defined as being the length of the opposite side divided by the length of the hypotenuse. The six trigonometric functions are defined for every real number , except, for some of them, for angles that differ from 0 by a multiple of the right angle (90°).

  9. Jaccard index - Wikipedia

    en.wikipedia.org/wiki/Jaccard_index

    In other contexts, where 0 and 1 carry equivalent information (symmetry), the SMC is a better measure of similarity. For example, vectors of demographic variables stored in dummy variables, such as gender, would be better compared with the SMC than with the Jaccard index since the impact of gender on similarity should be equal, independently of ...