StratifiedSampling.md (667B)
1 # Stratified Sampling 2 3 ML CH2 4 5 **Definition:** Stratified sampling is the process of selecting samples based on the likelihood of samples being from strata. 6 7 This is often used when there are smaller sample sizes that can't guarantee an accurate representative sample for testing and training data. We then define some strata and try to ensure accurate representation from each grouping to get more generalizable data. 8 9 When you do sampling to make sure you get the correct ratios of data from each stratum this is called proportionate allocation whereas there is also optimum allocation or disproportionate allocation where we try to minimize variance (deviation).