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Hyperparameter

Definition

A configuration that is external to the model and whose value cannot be estimated from data.

Deep Dive

A hyperparameter is a configuration variable that is external to a machine learning model and whose value cannot be estimated from the data itself. Unlike model parameters, which are learned during the training process (e.g., weights and biases in a neural network), hyperparameters are set by the data scientist *before* training begins and dictate how the model learns or its overall architecture.

Examples & Use Cases

  • 1The learning rate in a neural network, which controls the step size during optimization
  • 2The number of clusters (k) to form in a K-Means clustering algorithm
  • 3The maximum depth of a decision tree in a classification model

Related Terms

Model ParameterMachine LearningModel Tuning

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