Ghost: Missing Data Segments Imputation in Multivariate Streams

Helper functions provide an accurate imputation algorithm for reconstructing the missing segment in a multi-variate data streams. Inspired by single-shot learning, it reconstructs the missing segment by identifying the first similar segment in the stream. Nevertheless, there should be one column of data available, i.e. a constraint column. The values of columns can be characters (A, B, C, etc.). The result of the imputed dataset will be returned a .csv file. For more details see Reza Rawassizadeh (2019) <doi:10.1109/TKDE.2019.2914653>.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: R6
Published: 2020-03-25
DOI: 10.32614/CRAN.package.Ghost
Author: Siyavash Shabani, Reza Rawassizadeh
Maintainer: Siyavash Shabani <s.shabani.aut at>
License: GPL-3
NeedsCompilation: no
CRAN checks: Ghost results


Reference manual: Ghost.pdf


Package source: Ghost_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): Ghost_0.1.0.tgz, r-oldrel (arm64): Ghost_0.1.0.tgz, r-release (x86_64): Ghost_0.1.0.tgz, r-oldrel (x86_64): Ghost_0.1.0.tgz


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