Classical Machine Learning
Which digit do the scores support?
BOTIE
Examples, experiments and workspace controls
Connect a tool's inputs to see what it produces. You can try a branch before connecting it to Result.
Try your own inputs
Use a copy of the example to try your own data. Keep the problem's assumptions in mind, and predict the effect of a change before checking the output. You can also add another branch to compare two ways of doing the calculation.
Context for this challenge
Turn the scores for digits 0, 1 and 2 into positive probabilities that sum to one. Build the exponentiation, total and division yourself.
The handwriting recogniser has competing scores for digits 0, 1 and 2. Botie needs positive shares that describe one joint decision.
Exponentiate the score vector, total those contributions and divide each contribution by the shared total.
Examples and results
- Scores for digits 0, 1 and 2
- 0-2
- 11
- 23
- Required result
- 00.0059
- 10.1185
- 20.8756
- Scores for digits 0, 1 and 2
- 00
- 12
- 21
- Required result
- 00.09
- 10.6652
- 20.2447
Try a fresh construction
This clears this draft, including its undo history. Earlier successful attempts stay recorded. Build again without opening hints to record an independent attempt.
Stuck? Inspect a worked construction
The tools below form one possible solution. You can assemble it, follow its signals, and undo that change to return to your own construction.
Assumptions and test precision
This is a small construction problem. The lesson explains the assumptions and the parts of the full method that this example leaves out. Numerical tests allow a difference of 0.001. Lists and structures must also have the right shape.
Three unequal but moderate digit scores
This check uses the pieces from “Normalise the three digits' positive contributions”.
BOTIE
- Scores for digits 0, 1 and 2
- 00
- 10.6931
- 21.0986
Use a number, text, or an array matching the requested result. For a matrix, put each row in brackets. Saving your prediction runs your current construction on these inputs and checks the earlier examples too.
Build a construction in the workspace above first. This case will test those pieces.
Why can one digit's probability fall even if its own score stays fixed while a competing score rises?
For mutually exclusive classes, probability conversion must account for the competing alternatives together.
This is a small construction problem. The lesson explains the assumptions and the parts of the full method that this example leaves out.
Work through the Python challenges →