Building, comparing, and optimizing models.
Now we are moving to the second part of our project on Machine Learning Model Selection in Multivariate Analysis with Anonymized Data.
This second part is where the glamour comes in — predictive modeling, machine learning. Everyone is eager to jump straight into building machine learning models. I get that, and I feel the same excitement because I love this stage.
But before we get there, we must go through data processing — which is exactly what we covered in the previous tutorial.
We begin by installing the XGBoost package, one of the favorites among those who participate in Machine Learning competitions on the Kaggle platform.
# This package does not come with Anaconda and needs to be installed
!pip install -q xgboost
This package doesn’t come with Anaconda, so you need to install it separately. To…
