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2009

Data Mining in Incomplete Numerical and Categorical Data Sets: A Neuro Fuzzy Approach

9 years 4 days ago
Data Mining in Incomplete Numerical and Categorical Data Sets: A Neuro Fuzzy Approach
- There are many applications dealing with incomplete data sets that take different approaches to making imputations for missing values. Most tackle the problem for numerical input variables in the data set. However, when there are two types of input variables, numerical and categorical, the state of the art has provided no clear solutions. This paper presents a proposal for handling incomplete numerical and categorical data sets using an extension of an existing neuro-fuzzy approach. The method is extensively tested in a real environment in the field of the political election polls.
Pilar Rey del Castillo, Jesus Cardenosa
Added 18 Feb 2011
Updated 18 Feb 2011
Type Journal
Year 2009
Where ICAI
Authors Pilar Rey del Castillo, Jesus Cardenosa
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