A comparison of imputation methods in the presence of imprecise data when employing a neural network s-Sigmoid function

ISSN： 1743-8187

Source： International Journal of Business Intelligence and Data Mining, Vol.2, Iss.3, 2007-10, pp. : 292-310

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

A comparison of model-based and neural network-based diagnostic methods

By Rengaswamy R. Mylaraswamy D. Årzen K.-E. Venkatasubramanian V.

Engineering Applications of Artificial Intelligence, Vol. 14, Iss. 6, 2001-12 ,pp. : 805-818

Elsevier

Access to resources Recommend Favorite

Combining Data Preprocessing Methods With Imputation Techniques for Software Defect Prediction

International Journal of Open Source Software and Processes (IJOSSP), Vol. 9, Iss. 1, 2018-01 ,pp. : 1-19

IGI Global_journal

Access to resources Recommend Favorite

A comparison of linear regression and neural network methods for predicting excess returns on large stocks

By desai V.S. Bharati R.

Annals of Operations Research, Vol. 78, Iss. 1, 1998-01 ,pp. : 127-163

Springer Publishing Company

Access to resources Recommend Favorite

Missing Data Imputation Techniques

By Song Qinbao Shepperd Martin

International Journal of Business Intelligence and Data Mining, Vol. 2, Iss. 3, 2007-10 ,pp. : 261-291

Inderscience Publishers

Access to resources Recommend Favorite

Reduction of complexity in conic section function neural network

By O¨zylmaz Lale Yldrm Tu¨lay

Kybernetes: The International Journal of Systems & Cybernetics, Vol. 32, Iss. 4, 2003-04 ,pp. : 540-547

Emerald Group Publishing Ltd

Access to resources Recommend Favorite