Recommending Training Set Sizes for Classification

Understand

Based on a comprehensive study of 20 established data sets, we recommend training set sizes for any classification data set.

• We obtain our recommendations by systematically withholding training data and developing models through five different classification methods for each resulting training set.
• Based on these results, we construct accuracy confidence intervals for each training set size and fit the lower bounds to inverse power low learning curves.
• We also estimate a sufficient training set size (STSS) for each data set based on established convergence criteria.