When reading the documentation of Random Forest, I got the following: ``` max_samples : int or float, default=None If bootstrap is True, the number of samples to draw from X to train each base estimator. - *If None (default), then draw `X.shape[0]` samples.* - If int, then draw `max_samples` samples. - If float, then draw `max_samples * X.shape[0]` samples. Thus, `max_samples` should be in the interval `(0, 1)`. ```
Why does the whole dataset (i.e. X.shape[0] samples from X) is used to build each tree? That would be equivalent to bootstrap to be False, right? Wouldn't it be better practices to use as default 2/3 of the size of the dataset?
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