Model parameters vs. hyperparameters
In order to perform hyperparameter tuning, it is important to really understand what hyperparameters are (and what they are not). So let's look at model parameters versus hyperparameters in detail.
Note: The Breast Cancer Wisconsin (Diagnostic) dataset has been loaded as breast_cancer_data
for you.
This exercise is part of the course
Hyperparameter Tuning in R
Exercise instructions
- Use this dataset to fit a linear model with
concavity_mean
as response andsymmetry_mean
as predictor variable. - Look at the
summary()
of this linear model. - Extract the coefficients.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Fit a linear model on the breast_cancer_data.
linear_model <- ___(___)
# Look at the summary of the linear_model.
___
# Extract the coefficients.
___