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) .


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install.packages("Ghost")

0.1.0 by Siyavash Shabani, 15 days ago


https://www.researchgate.net/publication/332779980_Ghost_Imputation_Accurately_Reconstructing_Missing_Data_of_the_Off_Period


Browse source code at https://github.com/cran/Ghost


Authors: Siyavash Shabani , Reza Rawassizadeh


Documentation:   PDF Manual  


GPL-3 license


Imports R6


See at CRAN