The University of California at Irvine's Categorisation Benchmark
- Everyone uses the UCI benchmark, so you can compare your
algorithm to other algorithms.
- It's here.
- We're going to look at a toy data set, baloons.
- Instances are typically represented by a vector of feature values,
and a category.
- Here there are four (binary) features, and a binary category.
- What other types of features could you have?
Colour | Size | Act | Age | Category/Inflated |
YELLOW | SMALL | STRETCH | ADULT | T |
YELLOW | SMALL | STRETCH | CHILD | F |
YELLOW | SMALL | DIP | ADULT | F |
YELLOW | SMALL | DIP | CHILD | F |
YELLOW | LARGE | STRETCH | ADULT | T |
YELLOW | LARGE | STRETCH | ADULT | T |
YELLOW | LARGE | STRETCH | CHILD | F |
YELLOW | LARGE | DIP | ADULT | F |
YELLOW | LARGE | DIP | CHILD | F |
PURPLE | SMALL | STRETCH | ADULT | T |
PURPLE | SMALL | STRETCH | ADULT | T |
PURPLE | SMALL | STRETCH | CHILD | F |
PURPLE | SMALL | DIP | ADULT | F |
PURPLE | SMALL | DIP | CHILD | F |
PURPLE | LARGE | STRETCH | ADULT | T |
PURPLE | LARGE | STRETCH | ADULT | T |
PURPLE | LARGE | STRETCH | CHILD | F |
PURPLE | LARGE | DIP | ADULT | F |
PURPLE | LARGE | DIP | CHILD | F |