@inproceedings{eac9a67b20384bc7b6df6b665d6f27e2,
title = "A New Method for Estimation of Missing Data Based on Sampling Methods for Data Mining",
abstract = "Today we collect large amounts of data and we receive more than we can handle, the accumulated data are often raw and far from being of good quality they contain Missing Values and noise. The presence of Missing Values in data are major disadvantages for most Datamining algorithms. Intuitively, the pertinent information is embedded in many attributes and its extraction is only possible if the original data are cleaned and pre-treated. In this paper we propose a new technique for preprocessing data that aims to estimate Missing Values, in order to obtain representative Samples of good qualities, and also to assure that the information extracted is more safe and reliable.",
keywords = "Copulas, Datamining, Missing Value, Multidimensional Sampling, Sampling",
author = "Rima Houari and Ahc{\'e}ne Bounceur and Tahar Kechadi and Tari Abdelkamel and Reinhardt Euler",
year = "2013",
doi = "10.1007/978-3-319-00951-3_9",
language = "English",
isbn = "9783319009506",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
number = "1",
pages = "89--100",
booktitle = "Advances in Computational Science, Engineering and Information Technology - Proceedings of the Third International Conf. on Computational Science,Engineering and Information Technology, CCSEIT-2013",
address = "Germany",
edition = "1",
note = "3rd International Conference on Computational Science, Engineering and Information Technology, CCSEIT 2013 ; Conference date: 07-06-2013 Through 09-06-2013",
}