This post provides some useful resources about fine tuning parameters using grid search for machine learning and deep learning models.
- How to Grid Search Hyperparameters for Deep Learning Models in Python With Keras (by on August 9, 2016 in Deep Learning) — pdf
- Cross Validation With Parameter Tuning Using Grid Search (by Chris Albon, Dec20, 2017) — pdf
This post used SVM as example, see here for SVM.SVC example.
- SVM Parameter Tuning in Scikit Learn using GridSearchCV (by Aneesha Bakharia, Jan 17, 2016) — pdf
- Tuning the hyper-parameters of an estimator
- Compare randomized search and grid search for optimizing hyperparameters of a random forest.
- Hyperparameter Tuning the Random Forest in Python (by William Koehrsen, Jan 9, 2018) — pdf
- How to tune hyperparameters with Python and scikit-learn (by on August 15, 2016 in Machine Learning, Tutorials) — pdf
This post used k-NN as an example for grid search.
- TBA
