Computer Science
8 months ago

Elastic Net Method Reduces Infant Mortality Rates in South Sulawesi

Jurnal Matematika Statistika dan Komputasi
Comparative Analysis of Ridge, LASSO, and Elastic Net Regularization Approaches in Handling Multicollinearity for Infant Mortality Data in South Sulawesi
Arief Rahman Nur, Andi Kresna Jaya, Siswanto Siswanto

Paper Summary

Related papers

Theme background image
Computer Science
8 months ago

Elastic Net Method Reduces Infant Mortality Rates in South Sulawesi

Data Mining
1 view
Theme background image
Mathematics
2 years ago

Lasso Regression Outperforms Ridge in Predicting Covid-19 Impact in Kurdistan

COVID-19 Modeling
Theme background image
Mathematics
2 years ago

Bridge regression outperforms Elastic Net in handling multicollinearity for better predictions.

Multicollinearity
Chemometrics
Regularization Methods

Infant mortality rates are important for understanding health and care quality. Researchers compared three methods to analyze data from South Sulawesi. Ridge regression controls variance, LASSO selects variables, and elastic net combines both. Elastic net performed best, with a 60.81% accuracy rate, beating ridge (54.11%) and LASSO (58.18%).