Amanote Research

Amanote Research

  • Register
  • Sign In

Fuzzy Min–max Neural Networks for Categorical Data: Application to Missing Data Imputation

Neural Computing and Applications- United Kingdom

doi 10.1007/s00521-011-0574-x

Full Text

Abstract

Available in

Categories

Artificial IntelligenceSoftware

Date

March 27, 2011

Authors

Pilar Rey-del-CastilloJesús Cardeñosa

Publisher

Springer Science and Business Media LLC


Related search

Missing Data Imputation for Ordinal Data

International Journal of Computer Applications
2018English

Contributions to Imputation for Missing Survey Data

English

Low-Dimensional Models for Missing Data Imputation in Road Networks

2013English

Agglomerative Learning for General Fuzzy Min-Max Neural Network

English

Iris Recognition Using Fuzzy Min-Max Neural Network

International Journal of Computer and Electrical Engineering
2011English

Neural Models for Imputation of Missing Ozone Data in Air-Quality Datasets

Complexity
MultidisciplinaryComputer Science
2018English

Missing Data Imputation Method for Autism Prediction

International Journal of Recent Technology and Engineering
EngineeringManagement of TechnologyInnovation
2020English

Robust Regression Imputation for Analyzing Missing Data

2012English

Correction To: MISC: Missing Imputation for Single-Cell RNA Sequencing Data

BMC Systems Biology
Molecular BiologyApplied MathematicsStructural BiologySimulationComputer Science ApplicationsModeling
2019English

Amanote Research

Note-taking for researchers

Follow Amanote


© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy