Interactive: Logistic Regression — drag the sigmoid + decision boundary
DRAG the weight + bias sliders. SEE the sigmoid curve shift. SEE the decision boundary move. SEE how probability changes for each data point.
interactive.lab
v3.1
Drag the sliders — see the graph update in real-time
Live interactive chart
drag sliders → graph updates
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🧠 How it works
INTERACTIVE LOGISTIC REGRESSION: The sigmoid is the HEART of logistic regression. weight (w) controls how STEEP the curve is. High weight = sharp transition (very confident). Low weight = gradual transition (uncertain). bias (b) shifts the curve LEFT/RIGHT. Positive bias = boundary moves left (predict 1 more often). Negative bias = boundary moves right (predict 0 more often). The decision boundary is at x = -bias/weight. Try to find the weight + bias that best separates the blue and red dots!
✏️ Try these changes
-
Set weight=5 — very steep curve→ sharp decision boundary, very confident predictions -
Set weight=0.1 — almost flat curve→ predictions are always ~0.5, useless model -
Set bias=-3 — boundary moves right→ predicts class 0 for more of the data -
Set weight=-2 — negative relationship→ curve flips — predicts 1 on the LEFT