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>.

Getting started

Package details

AuthorSiyavash Shabani, Reza Rawassizadeh
MaintainerSiyavash Shabani <>
Package repositoryView on CRAN
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Ghost documentation built on March 26, 2020, 6:45 p.m.