Averaging is usually used for regression problems or can be used while estimating the probabilities in classification tasks. Predictions are extracted from multiple models and an average of the predictions are used to make the final prediction.
Let us get ready to build multiple learners and see how to implement averaging:
Download the whitewines.csv dataset from GitHub and copy it to your working directory, and let's read the dataset:
df_winedata = pd.read_csv("whitewines.csv")
Let's take a look at the data with the following code:
In the following screenshot, we can see that the data has been read properly: