Hoeffding Tree Split Confidence

Compare a split-merit gap with a shrinking confidence threshold before growing a stream tree.

Experiment

Open the Hoeffding Tree Split Confidence module to test how the number of observations and the allowed error rate affect the split decision.

1. Set Tables to "Strong", Count multiplier to 10, Delta to 0.05, and Tie threshold to 0. Notice the Gap (0.16) is larger than the Hoeffding epsilon (0.0865), resulting in a "Split by merit gap" decision.
2. Change the Count multiplier to 1. The total observations drop to 20, causing the Hoeffding epsilon to increase to 0.273. Because epsilon is now larger than the Gap (0.16), the decision becomes "Defer" to wait for more data.
3. Set Tables to "Weak", Count multiplier to 100, and Delta to 0.05. Here the Gap is only 0.02, while epsilon shrinks to 0.0273. The decision remains "Defer".
4. To force a split despite similar merits, change the Tie threshold to 0.05. Since the epsilon (0.0273) falls below this threshold, the algorithm uses the "Split by tie heuristic" decision, avoiding infinite deferrals when features are nearly identical.