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Semblance

A Data-Driven Similarity Kernel on Probability Spaces

v1.1.0 · Jan 25, 2019 · GPL-2

Description

We present a rank-based Mercer kernel to compute a pair-wise similarity metric corresponding to informative representation of data. We tailor the development of a kernel to encode our prior knowledge about the data distribution over a probability space. The philosophical concept behind our construction is that objects whose feature values fall on the extreme of that feature’s probability mass distribution are more similar to each other, than objects whose feature values lie closer to the mean. Semblance emphasizes features whose values lie far away from the mean of their probability distribution. The kernel relies on properties empirically determined from the data and does not assume an underlying distribution. The use of feature ranks on a probability space ensures that Semblance is computational efficacious, robust to outliers, and statistically stable, thus making it widely applicable algorithm for pattern analysis. The output from the kernel is a square, symmetric matrix that gives proximity values between pairs of observations.

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Maintainer: ‘Divyansh Agarwal <divyansh@upenn.edu>’

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  Authors@R: c(person(given = c("Divyansh", "Agarwal", "Nancy", "R.", "Zhang"),
                      family = "<nzh@wharton.upenn.edu>",
                      role = "aut",
                      email = "nzh@wharton.upenn.edu"),
               person(given = "Divyansh",
                      family = "Agarwal",
                      role = "cre",
                      email = "divyansh@upenn.edu"))
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Maintainer: ‘Divyansh Agarwal <divyansh@upenn.edu>’

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  Authors@R: c(person(given = c("Divyansh", "Agarwal", "Nancy", "R.", "Zhang"),
                      family = "<nzh@wharton.upenn.edu>",
                      role = "aut",
                      email = "nzh@wharton.upenn.edu"),
               person(given = "Divyansh",
                      family = "Agarwal",
                      role = "cre",
                      email = "divyansh@upenn.edu"))
as necessary.
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NOTE 9 OK · 5 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Divyansh Agarwal <divyansh@upenn.edu>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = c("Divyansh", "Agarwal", "Nancy", "R.", "Zhang"),
                      family = "<nzh@wharton.upenn.edu>",
                      role = "aut",
                      email = "nzh@wharton.upenn.edu"),
               person(given = "Divyansh",
                      family = "Agarwal",
                      role = "cre",
                      email = "divya
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Divyansh Agarwal <divyansh@upenn.edu>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = c("Divyansh", "Agarwal", "Nancy", "R.", "Zhang"),
                      family = "<nzh@wharton.upenn.edu>",
                      role = "aut",
                      email = "nzh@wharton.upenn.edu"),
               person(given = "Divyansh",
                      family = "Agarwal",
                      role = "cre",
                      email = "divya
NOTE r-oldrel-macos-arm64

LazyData

  'LazyData' is specified without a 'data' directory
NOTE r-oldrel-macos-x86_64

LazyData

  'LazyData' is specified without a 'data' directory
NOTE r-oldrel-windows-x86_64

LazyData

  'LazyData' is specified without a 'data' directory

Dependency Network

Dependencies Reverse dependencies fields PerformanceAnalytics DescTools msos Semblance

Version History

new 1.1.0 Mar 9, 2026