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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

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Exercise instructions

  • Use this dataset to fit a linear model with concavity_mean as response and symmetry_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.
___
Edit and Run Code