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) .


Reference manual

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0.1.0 by Siyavash Shabani, 15 days ago


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