Anomaly Detection
Score isolation paths
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
Average paths, divide by the normaliser, negate, then raise two to that exponent.
Botie has each fitted tree's isolation path length for one reading. Short paths indicate that relatively few partitions separated it.
Average the tree paths, divide by the supplied positive normaliser, negate, and raise two to that exponent.
Examples and results
- Paths across trees
- 01
- 11
- Positive c(n)
2
- Required result
0.7071
- Paths across trees
- 02
- 12
- Positive c(n)
2
- Required result
0.5
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
Paths must come from fitted trees with a consistent subsample size and leaf correction policy. Numerical tests allow a difference of 0.001. Lists and structures must also have the right shape.
Some trees isolate the reading sooner
This check uses the pieces from “Convert isolation paths into a comparable score”.
BOTIE
- Paths across trees
- 02
- 14
- 26
- Positive c(n)
4
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 should path lengths from incompatible subsample sizes not share an arbitrary normaliser?
An isolation score depends on the fitted trees' sampling and path-correction conventions.
Paths must come from fitted trees with a consistent subsample size and leaf correction policy.
Work through the Python challenges →