Evaluating and Improving Models
Diagnose Botie’s temperature predictions
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
Return one observed-minus-predicted residual per morning, keeping their signs.
Zero signed error has concealed mistakes in both directions.
Inspect the component calculation
Observed minus predicted( Observed values: Observed temperatures Predictions: Predicted temperatures )
Examples and results
- Observed temperatures
- 012
- 116
- Predicted temperatures
- 010
- 118
- Required result
- 02
- 1-2
- Observed temperatures
- 05
- 17
- Predicted temperatures
- 08
- 110
- Required result
- 0-3
- 1-3
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
Supplied predictions make the arithmetic inspectable. These tiny fixtures do not estimate deployment performance. Numerical tests allow a difference of 0.001. Lists and structures must also have the right shape.
Your last tested pieces can start the full construction. An existing draft there keeps its own pieces.
Mixed errors with a negative mean
This check uses the pieces from “Measure direction and size separately”.
BOTIE
- Observed temperatures
- 02
- 16
- 210
- Predicted temperatures
- 04
- 15
- 212
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.
What additional column would help explain why the large miss occurred?
Keep observation identity and relevant conditions with each residual.
Supplied predictions make the arithmetic inspectable. These tiny fixtures do not estimate deployment performance.
Work through the Python challenges →