A Three-Way Interplay: Model Complexity, Sample Size, and Data Dimensionality
This interactive tool helps you explore how model complexity (Decision Tree depth), training sample size, and data dimensionality (feature set) shape performance on UCI Irvine – Predict Students’ Dropout and Academic Success dataset. Adjust the controls and see how overfitting/underfitting emerge. Extensive experimentation will help you build an intuition for diagnosing and fixing models when…