For K-12 Students · Logistic Regression
Logistic Regression for a clustering model
Built for k-12 students learning it in middle or high school. Watch the idea come alive with plain-language steps and everyday examples — perfect for projects and homework. Simulate a clustering model live below — adjust the inputs and watch it respond, right in your browser.
Logistic RegressionLive
probability from a straight line
Controls
Presets
Logistic regression squashes a linear score through the sigmoid to output a probability between 0 and 1. Predictions above the threshold become one class, below it the other. Raising the weight sharpens the S-curve into a harder decision. Educational tool.
Data Inspector
Decision boundary at x0.50
P(class 1 | x=1)0.82
Threshold0.50
Governing equation
Reading this result: Logistic regression fits this sigmoid by gradient descent on cross-entropy. Weight w=3 sets steepness, bias b=-1.5 shifts the curve, placing the decision boundary at x=0.50 for threshold 0.5.
Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.
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Frequently asked questions
- Is this good for k-12 students?
- Yes — this version of "Logistic Regression for a clustering model" is framed for k-12 students learning it in middle or high school. Watch the idea come alive with plain-language steps and everyday examples — perfect for projects and homework.
- Do I need to install anything?
- No. It runs in any modern browser, free, with no account required.