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Wednesday, July 6, 2022

Hyper Parameter Tuning of Decision Tree


 What is Hyper Parameter tuning?

Hyperparameter tuning is searching the hyperparameter space for a set of values that will optimize your model architecture

How to Determine HyperParameters?

Hyperparameter tuning is  tricky as there is no direct way to calculate how a change in the hyperparameter value will reduce the loss of your model, so we usually resort to experimentation


Define range of possible values for all the hyperparameters.

To Determine range first  understand what these hyperparameters mean and how changing a hyperparameter will affect your model architecture, thereby try to understand how your model performance might change.

Step: 2

Apply GridSearch(common and expensive) ,or smarter and less expensive methods like Random Search and Bayesian Optimization to determine the Parameters.

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