International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 183 - Number 53 |
Year of Publication: 2022 |
Authors: Madhu H.K., D. Ramesh |
10.5120/ijca2022921945 |
Madhu H.K., D. Ramesh . Dimensionality Reduction of Healthcare Data through Niche Genetic Algorithm. International Journal of Computer Applications. 183, 53 ( Feb 2022), 7-11. DOI=10.5120/ijca2022921945
Technology into medical health care has generated voluminous parameters for human physiological condition, forming data for high dimensions. Data which is raw makes any computing techniques complex and it is not structured.Structuring data can be a pre-processing model,but extracting useful parameters which contribute to reducing the computational complexities of any intelligent algorithm for classification and prediction is a big challenge in technology. Dimensionality reduction is a common strategy adopted by research to select appropriate parameters for further computations. In this research work Niche genetic algorithm is implemented on various healthcare datasets which extracts relevant parameters for classification and prediction of healthcare data with reduced computation complexity and increased accuracy. The proposed model is independent of any application, but restricts to structured data.