# AI News, BOOK REVIEW: What is resampling in machine learning?

## What is resampling in machine learning?

Re-sampling is a series of methods used to reconstruct your sample data sets, including training sets and validation sets.

For example, in Random Forest Algorithm, we can assume that we only have a training set $\cal{D}$ with $N$ samples in it, and now we need to construct $T$ decision trees by iterating the learning process for $T$ times.

The aggregation of different trees learning from separately re-sampling training sets can achieve higher accuracy and avoid overfitting to some extent.

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