Hyperparameter Optimization Techniques for Data Science Hackathons

For the python code, I used the Iris dataset which is available within the Scikit-learn package. It is a very small dataset (150 rows only) with a multiclass classification problem. As we are mostly focussing on hyperparameter tuning, I have not performed the EDA(exploratory data analysis) or feature engineering part and directly jumped into the model-building. I used the XGBoostClssifier algorithm for the model-building to classify the target variables. GridSearchCV is a function that comes in Scikit-learn's(or SKlearn) model_selection package.To use the GridSearchCV function, first, we define a dictionary in which we mention a particular hyperparameter along with the values it can take.