Classical Machine Learning
Is the closest match convincing?
The second candidate nearly ties the first
A descriptor always has some nearest candidate, but a nearly tied second candidate makes that match ambiguous. Botie needs a relative distance check.
BOTIE
The inputs we are comparing
Query descriptor
Same in both cases
- 00
- 10
Candidate descriptors
Example 1
| 1 | 0 |
| 3 | 0 |
| 5 | 0 |
Example 2
| 1 | 0 |
| 1.1 | 0 |
| 5 | 0 |
Result for example 1
1
The descriptor ratio reaches the cutoff exactly
This check uses the pieces from “Require the nearest descriptor to be clearly closer”.
BOTIE
- Query descriptor
- 01
- 11
- Candidate descriptors
5 1 6 1 11 1
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 does a close runner-up matter more than a very distant third candidate, and why do the square roots belong before the ratio comparison?
A nearest-match decision may need an ambiguity test in the same distance convention as its stated threshold.
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 →