Training CV

Description

Training a CV involves testing all possible hyperparameters in each attempt. The process consists of the following steps:

1. Define the hyperparameters and their search space: Identify the hyperparameters to optimize and specify their possible value ranges.

2. Choose a search strategy: Select a method to explore the hyperparameter search space, such as:

   • Grid search: Systematically evaluates all possible hyperparameter combinations.
   • Random search: Samples random combinations within the search space.
   • Bayesian optimization: Uses a probabilistic model to guide the search, balancing exploration and exploitation.

3. Perform the search: Train a model using each combination of hyperparameter values and evaluate its performance.

4. Select the best hyperparameters: Choose the combination that achieves the best performance based on the evaluation metric.