OPTIMASI HYPERPARAMETER PADA GRADIENT BOOSTED TREES MENGGUNAKAN BAYESIAN OPTIMIZATION
Daftar Isi:
- Data mining is a technique to transform a collection of data into a knowledge. One of the factors that affect the accuracy of these data mining methods is hyperparameters which must be determined before training proses started. The data mining method that is very affected by hyperparameters is Gradient Boosted Trees. With a wrong hyperparameter configuration, the Gradient Boosted Tree model will be overfitting. One way that can be used to prevent this is to optimize Gradient Boosted Trees hyperparameters with hyperparameter optimization techniques and one of the popular hyperparameter optimization methods is Bayesian Optimization. Therefore, this study utilizes Bayesian Optimization to optimize Gradient Boosted Trees hyperparameter.