Sweep Parameters
Create an ML model with sweep hyperparameters.
We'll cover the following...
Selecting the sweep parameters
We often test with various parameters when we develop the ML model. Creating multiple experiments with a combination of hyperparameter values is a tedious task. Instead, we can create one sweep job that tries all the possible combinations and selects the best model. We will be using SVM here and using a sweep job for hyperparameter tuning.
The hyperparameters need to be defined using searchspace.
The option type specifies how to choose different values. We use choice for categorical values, which means choosing one of the values defined. We can use distribution methods like uniform and randint for integer values. ...