A randomized-grid hybrid hyperparameter tuner is proposed and claimed to outperform standard grid and random search in both accuracy and training time for CVD classification models.
The consistent increase in CVDs prevalence, influenced by the factors such as aging, population’s lifestyle changes along with the regional factors also has significant role in it
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Time-Efficient Hybrid Hyperparameter Tuning Approach for Cardiovascular Disease Classification
A randomized-grid hybrid hyperparameter tuner is proposed and claimed to outperform standard grid and random search in both accuracy and training time for CVD classification models.