First, we perform the data processing and understand the features used in the dataset.
We used various ML algorithms for Airfoil-self-noise-prediction. For each ML model, we performed Hyperparameter tuning to get the better models and report the better models.
Here are the algorithms used:
- Linear regression
- Lasso
- Ridge
- Decision Tree
- Random Forest
- Gradient Boosting
- Support vector
- KNN
- XGBoost
Before Hyperparameter tuning, the results are as follows:
Here are the Hyperparameters used for each model we tested
Before Hyperparameter tuning, the results are as follows:
