ML Cross-Validation Strategies
Compare k-fold, stratified, group, and time-series cross-validation so your offline scores actually predict production performance.
·4 min read · #ml#cross-validation#kfold
3 posts · page 1 of 1
Compare k-fold, stratified, group, and time-series cross-validation so your offline scores actually predict production performance.
Work with datetime indexes, resampling, rolling windows, lag features, and timezone gotchas to analyze time series cleanly in pandas.
Use Pandas rolling, expanding, and ewm window functions to compute moving averages, running totals, and time-aware aggregations with clear examples.