What is a decision tree?

02 · See it in action

Follow the steps

1. Draw a two-question rule for a synthetic task.
2. Fit a shallow tree and inspect its splits.
3. Compare it with a deeper tree on held-out data.
4. Look at the number of examples reaching each leaf.

Worked example

from sklearn.tree import DecisionTreeClassifier
x = [[10], [15], [40], [45]]
y = [1, 1, 0, 0]
m = DecisionTreeClassifier(max_depth=1, random_state=7).fit(x, y)
print(m.predict([[12], [42]]))  # [1 0]

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