Estimation of missing values using optimized hybrid fuzzy c-means and majority vote for microarray data. Journal of Information and Communication Technology (JICT), 19 (4). pp. 459-482. ISSN 2180-3862 (2020)
Abstract
Missing values are a huge constraint in microarray technologies towards improving and identifying disease-causing genes. Estimating missing values is an undeniable scenario faced by field experts. The imputation method is an effective way to impute the proper values to proceed with the next process in microarray technology. Missing value imputation methods may increase the classification accuracy. Although these methods might predict the values, classification accuracy rates prove the ability of the methods to identify the missing values in gene expression data. In this study, a novel method, Optimised Hybrid of Fuzzy C-Means and Majority Vote (opt-FCMMV), was proposed to identify the missing values in the data. Using the Majority Vote (MV) and optimisation through Particle Swarm Optimisation (PSO), this study predicted missing values in the data to form more informative and solid data
| Item Type: | Article |
|---|---|
| Keywords: | Fuzzy C-means,, Microarray data, Data optimization, Majority vote, Missing values |
| Taxonomy: | By Subject > Computer & Mathematical Sciences > Information Technology By Subject > Computer & Mathematical Sciences > Mathematics |
| Local Content Hub: | Subjects > Computer and Mathematical Sciences |
| Depositing User: | Muslim Ismail @ Ahmad |
| Date Deposited: | 23 Feb 2021 02:44 |
| Last Modified: | 23 Feb 2021 02:44 |
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