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Click to add a red data point
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R to retrain the model

Number of Trees = 100

Set this higher for smoother and more regularized final prediction. Higher is always better, but slower.

Max Depth = 4

Depth of each tree in the forest. Set this higher when more complicated decision boundaries are needed (but runs exponentially slower and can be more prone to overfitting if there are not enough trees). Usually if you can afford many trees and resources you want to set this higher.

Hypotheses per Node = 10

Number of random hypotheses considered at each node during training. Setting this too high puts you in danger of overfitting your data because nodes in the forest lose variety.