Karpagam Sundararajan
Biographic Data
| ID | 9894381 |
|---|---|
| NAME | Karpagam Sundararajan |
| GIVEN NAMES | Karpagam |
| FAMILY NAME | Sundararajan |
| SIGNATURE | SUNDARARAJAN K |
| AFFILIATIONS | Vellore Institute of Technology University |
| ORCID | 0000-0003-2094-9072 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
Performance Evaluation of Regression Models for the Prediction of the Covid-19 Reproduction Rate
This paper aims to evaluate the performance of multiple non-linear regression techniques, such as support-vector regression (SVR), k-nearest neighbor (KNN), Random Forest Regressor, Gradient Boosting, and XGBOOST for COVID-19 reproduction rate prediction and to study the impact of feature selection algorithms and hyperparameter tuning on prediction. Sixteen features (for example, Total_cases_per_million and Total_deaths_per_million) related to si…
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Performance Evaluation of Regression Models for the Prediction of the Covid-19 Reproduction Rate
This paper aims to evaluate the performance of multiple non-linear regression techniques, such as support-vector regression (SVR), k-nearest neighbor (KNN), Random Forest Regressor, Gradient Boosting, and XGBOOST for COVID-19 reproduction rate prediction and to study the impact of feature selection algorithms and hyperparameter tuning on prediction. Sixteen features (for example, Total_cases_per_million and Total_deaths_per_million) related to si…
Artificial Intelligence (1 work) · Computer Science (1 work) · COVID-19 diagnosis using AI (1 work) · COVID-19 epidemiological studies (1 work) · COVID-19 Pandemic Impacts (1 work) · Feature selection (1 work) · Gradient boosting (1 work) · Hyperparameter (1 work) · Linear regression (1 work) · Mathematics (1 work)