All work
Handwritten digit recognition with weighted KNN
A KNN classifier for handwritten digits, plus a k-value optimizer that collapses repeated distance calculations into a single pass.
- Type
- School
- Year
- 2020
- Built with
- Python · KNN · Optimization
Classify a handwritten digit from a 28×28 grid of pixels, each an integer
between 0 and 255. The KNN part is textbook. The part I actually cared about was
the cost of choosing k.
The naive approach re-runs the whole distance calculation for every candidate
value of k. I wrote an optimizer that reduces this to one instance of the
distance computation per unclassified object, then evaluates every candidate k
against those already-computed neighbours.
The full write-up, including the accuracy comparison across k values, is in the
research report.