Name a few hyper-parameters of decision trees?

Some hyperparameters of decision trees include:

• max_depth: Maximum depth of the tree.
• min_samples_split: Minimum number of samples required to split a node.
• min_samples_leaf: Minimum number of samples required in a leaf node.
• max_features: Maximum number of features to consider when splitting a node.
• criterion: The function used to measure the quality of a split (e.g., "gini" or "entropy").