What information entered the process?
Labs / Computer Science
Perceptron
Click anywhere to drop a point of the selected colour, then press Train. The perceptron nudges a straight decision boundary a little every time it meets a point on the wrong side, and misclassified points flash until the line finally separates blue from orange.
Labs / Computer Science / Perceptron
Perceptron
Click anywhere to drop a point of the selected colour, then press Train. The perceptron nudges a straight decision boundary a little every time it meets a point on the wrong side, and misclassified points flash until the line finally separates blue from orange.
Why it matters
Why explore this?
Computer science turns clear rules into reliable processes. This model lets you step through those rules and see how each decision changes the result.
Explore
Try the model
acc 100%epochs 0learning
Investigate
Questions to test
Predict first, try it in the model, then use what you observe to answer.
What to try
- Can the perceptron ever separate two classes that overlap, or does the line just keep swinging back and forth?
- What happens to the number of epochs when you crank the learning rate all the way up versus all the way down?
- Add a single blue point deep inside the orange cluster. How much does one stubborn outlier disturb the boundary?
- Arrange your points in a ring, blue inside and orange outside. Why can a single straight line never solve this?
- After it converges, drag the learning rate and add a new point on the wrong side — how quickly does it recover?
Explain
Make sense of what happened
Trace the process one step at a time. Name the rule used at each important step, then explain why the final result follows from those rules.
Check
Before you leave
Which rule changed it?
Why did the process produce this result?
If you can answer all three using evidence from the model, you understand the main idea. If not, return to Explore and change one setting at a time.