Creating a model using XGBoost with Auto Off
In this exercise, we are going to create a custom binary classification model using the XGBoost algorithm. You can achieve this by setting AUTO off. Here are the parameters that are available:
- AUTO OFF
- MODEL_TYPE
- OBJECTIVE
- HYPERPARAMETERS
For the complete list of hyperparameter values that are available and their defaults, please read the documentation found here:
https://docs.aws.amazon.com/redshift/latest/dg/r_create_model_use_cases.html#r_auto_off_create_model
Now that you have a basic understanding of the parameters available with XGBoost, you can create the model.
Creating a binary classification model using XGBoost
Let’s create a model to predict whether a transaction is fraudulent or non-fraudulent. As you learned in the previous chapters, creating models with Amazon Redshift ML is simply done by running a SQL command that creates a function. As inputs (or features), you will be using...
