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  2. File:Similarity analysis and clustering of modules.pdf

    en.wikipedia.org/wiki/File:Similarity_analysis...

    Testing various clustering algorithms and analyzing their results to find a suitable match for our task (determining which modules are similar and possible candidates to be merged). Also contains a brief literature review of code similarity detection. List of possible candidates for improvement of clustering using better algorithms.

  3. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    Similarity measures play a crucial role in many clustering techniques, as they are used to determine how closely related two data points are and whether they should be grouped together in the same cluster. A similarity measure can take many different forms depending on the type of data being clustered and the specific problem being solved.

  4. Analysis of similarities - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_similarities

    The test statistic R is calculated in the following way: R = r B − r W M / 2 {\displaystyle R={\frac {r_{B}-r_{W}}{M/2}}} where r B is the average of rank similarities of pairs of samples (or replicates) originating from different sites, r W is the average of rank similarity of pairs among replicates within sites, and M = n ( n − 1)/2 where ...

  5. Spearman's rank correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Spearman's_rank_correlation...

    Intuitively, the Spearman correlation between two variables will be high when observations have a similar (or identical for a correlation of 1) rank (i.e. relative position label of the observations within the variable: 1st, 2nd, 3rd, etc.) between the two variables, and low when observations have a dissimilar (or fully opposed for a ...

  6. Jaccard index - Wikipedia

    en.wikipedia.org/wiki/Jaccard_index

    Statistical inference can be made based on the Jaccard similarity index, and consequently related metrics. [6] Given two sample sets A and B with n attributes, a statistical test can be conducted to see if an overlap is statistically significant. The exact solution is available, although computation can be costly as n increases. [6]

  7. Point-biserial correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Point-biserial_correlation...

    follows Student's t-distribution with (n 1 +n 0 − 2) degrees of freedom when the null hypothesis is true. One disadvantage of the point biserial coefficient is that the further the distribution of Y is from 50/50, the more constrained will be the range of values which the coefficient can take.

  8. Rank correlation - Wikipedia

    en.wikipedia.org/wiki/Rank_correlation

    Dave Kerby (2014) recommended the rank-biserial as the measure to introduce students to rank correlation, because the general logic can be explained at an introductory level. The rank-biserial is the correlation used with the Mann–Whitney U test, a method commonly covered in introductory college courses on statistics. The data for this test ...

  9. Bhattacharyya distance - Wikipedia

    en.wikipedia.org/wiki/Bhattacharyya_distance

    In statistics, the Bhattacharyya distance is a quantity which represents a notion of similarity between two probability distributions. [1] It is closely related to the Bhattacharyya coefficient, which is a measure of the amount of overlap between two statistical samples or populations.