Another one with 40% of the reviews done is about active learning (here).
b) QUICK+ (under implementation): An unsupervised instance and feature selector, which works in two steps:
- Step1: Run QUICK on the dataset and find how many instances (q) you need.
- For q instances, transpose the dataset and find the popularity of features in a space defined by instances.
- Throw away features from least popular to most popular until there is a statistically significant deterioration in performance.
- Stop when performance drops significantly and put the last-thrown feature back.