Turn on each LEGO device, then connect it. Pick the motor first, then connect again and pick the sensor.
Motor: not connected
Sensor: not connected
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Sensor inputs
Tick every reading the model should compare on:
Simulation inputs
Motor position (training)
Mode TRAINING
Train a labeled example
Type a label name (e.g. "Cat" or "Bin A"), hand-position the arm/sensor for that example, then record it.
Live
Sensor: —
Motor: —
Recorded examples: 0
Examples per label (imbalance shows up here)
The Real Model looks at the 3 closest examples and votes. The Baseline ignores the sensor entirely and always guesses whichever label has the most examples.
Run mode — compare the guesses
Baseline guess
—
0 / 0—
Real model guess
—
0 / 0—
The arm physically moves to the real model's guess. The baseline is shown for comparison only. Tap Correct/Wrong after each new guess to track accuracy — try training a lopsided dataset (lots of one label, barely any of another) and watch the baseline's accuracy hold up misleadingly well, until you test the minority label.