Скачать или смотреть missing values in a dataset - how to impute them

A/Prof Zahid Islam of CSU, Australia describes how to impute (i.e. make an educated guess of) missing values in a data set using their technique called FIMUS.

Pre-print of the paper is available at:
https://www.researchgate.net/publicat...


The full reference to the paper is as follows:


Rahman, M. G., and Islam, M. Z. (2014): FIMUS: A Framework for Imputing Missing Values Using Co-appearance, Correlation and Similarity Analysis, Knowledge-Based Systems, Vol. 56, pp. 311-327, January 2014, DOI: 10.1016/j.knosys.2013.12.005 Available at http://dx.doi.org/10.1016/j.knosys.20...

Some other similar papers on missing value imputation are as follows

Rahman, M. G., and Islam, M. Z. (2013): Missing Value Imputation Using Decision Trees and Decision Forests by Splitting and Merging Records: Two Novel Techniques, Knowledge-Based Systems, Vol. 53, pp. 51 - 65, ISSN 0950-7051, DOI information: 10.1016/j.knosys.2013.08.023, Available at http://www.sciencedirect.com/science/...

Preprint of the above paper is available at: https://www.researchgate.net/publicat...

Rahman, M. G. and Islam, M. Z. (2011): A Decision Tree-based Missing Value Imputation Technique for Data Pre-processing, In Proc. of the Ninth Australasian Data Mining Conference (AusDM 11), Ballarat, Australia. December 01 - December 02, 2011, CRPIT, 121. Vamplew, P., Stranieri, A., Ong, K.-L., Christen, P. and Kennedy, P. J. Eds., ACS. 41-50

Preprint of the above paper is available at: https://www.researchgate.net/publicat...

More papers on related topics can be found at http://csusap.csu.edu.au/~zislam/