Yazdan Yasami

Evaluating the Effect of Tree Depth on the Performance of Decision Tree Classifiers

The maximum depth of a decision tree is one of the most influential hyperparameters governing the trade-off between model bias and variance. A tree that is too shallow may fail to capture the underlying structure of the data (underfitting), whereas a tree that is too deep tends t...

Evaluating the Effect of Tree Depth on the Performance of Decision Tree Classifiers

The maximum depth of a decision tree is one of the most influential hyperparameters governing the trade-off between model bias and variance. A tree that is too shallow may fail to capture the underlying structure of the data (underfitting), whereas a tree that is too deep tends t...