Volume 6, Issue sup1, January 1970, Pages 3 - 17
NIP - An Imperfection Processor to Data Mining datasets
JoséM. Cadenas, M. Carmen Garrido, Raquel Martínez
Available Online undefined.
- https://doi.org/10.1080/18756891.2013.818184How to use a DOI?
- Low quality data, imprecise/uncertain data, dataset with low quality data, Soft Computing, software tool for Soft Computing
- Every day there are more techniques that can work with low quality data. As a result, issues related to data quality have become more crucial and have consumed a majority of the time and budget of data mining projects. One problem for researchers is the lack of low quality data in order to test their techniques with this data type. Also, as far as we know, there is no software tool focused on the create/manage low quality datasets which treats, in the widest possible way, the low quality data and helps us to create repositories with low quality datasets for testing and comparison of data mining techniques and algorithms. For this reason, we present in this paper a software tool which can create/manage low quality datasets. Among other things, the tool can transform a dataset by adding low quality data, removing and replacing any data, constructing a fuzzy partition of the attributes, etc. It also allows different input/output formats of the dataset.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - JoséM. Cadenas AU - M. Carmen Garrido AU - Raquel Martínez TI - NIP - An Imperfection Processor to Data Mining datasets JO - International Journal of Computational Intelligence Systems SP - 3 EP - 17 VL - 6 IS - sup1 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2013.818184 DO - https://doi.org/10.1080/18756891.2013.818184 ID - Cadenasundefined ER -