What is a parameter?
A model parameter is a configuration variable internal to the model and whose value can be estimated from data. Parameters are essential to machine learning algorithms, and they are part of the model learned from historical training data. In classical machine learning literature, we may think of the model as the hypothesis and the parameters as the tailoring of the hypothesis to a specific set of data.
What are the characteristics of model parameters?
- They are required by the model when making predictions.
- Their values define the skill of the model on your problem.
- They are estimated or learned from data.
- They are often not set manually by the practitioner.
- They are often saved as part of the learned model.
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