Data, source code, documents and apps related to machine learning and color.
This material complements the recent CIC32 short course #09.
First, why machine learn colors?
The MNIST handwritten digits is a widely used machine learning dataset.
But color provides a nice complement to the MNIST data in the following ways :
colors | handwritten digits |
---|---|
A categorization problem | A classification problem |
No fixed number of categories | Fixed number of classes |
Includes multi-category (bluish green) | One class per digit |
5 to 10% adversarial data | No adversarial data |
Includes NSFW labels | Entirely SFW labels |
Red, green & blue as input | Image input |
Upper accuracy of 88% | Upper accuracy of 99.8% |
Token label | Character label |
Many misspellings | Not applicable |
Includes hapaxes | Not applicable |
A direct visualization attribute | Not applicable |
Categorical context | Nominal context (zip codes) |
Compatible with 3D LUTs | Not applicable |
Some entry points for this repository :