resampling

we performed resampling to reduce bias in the dataset.

bootstrapping is a common resampling technique for estimating confidence intervals.

the algorithm uses cross-validation with resampling to evaluate model performance.

data resampling can help address imbalanced class distributions in machine learning.

monte carlo simulation relies heavily on resampling random variables.

time series analysis often involves resampling to create overlapping segments.

stratified resampling ensures proportional representation of each group.

the study employed resampling to improve the statistical power of the analysis.

we conducted a sensitivity analysis using different resampling strategies.

jackknife resampling is useful for estimating bias and variance.

the goal of resampling is to obtain a more representative sample.