bootstrap sampling造句

例句与造句

1. Therefore, to resample cases means that each bootstrap sample will lose some information.
2. The number of bootstrap samples recommended in literature has increased as available computing power has increased.
3. The analysis was performed in bootstrap samples were used for each of the raw and trimmed means.
4. Also, it is possible that any particular bootstrap sample can contain more outliers than the estimator's breakdown point.
5. OOB is the mean prediction error on each training sample, using only the trees that did not have in their bootstrap sample.
6. It's difficult to find bootstrap sampling in a sentence. 用bootstrap sampling造句挺难的
7. Improvements to the LASSO include Bolasso which bootstraps samples, and FeaLect which scores all the features based on combinatorial analysis of regression coefficients.
8. The plots are based on 10, 000 bootstrap samples for each estimator, with some Gaussian noise added to the resampled data ( smoothed bootstrap ).
9. In some cases where exhaustive permutation resampling is performed, these tests provide exact, strong control of Type I error rates; in other cases, such as bootstrap sampling, they provide only approximate control.
10. A convolution method of regularization reduces the discreteness of the bootstrap distribution by adding a small amount of " N " ( 0, " ? " 2 ) random noise to each bootstrap sample.
11. This process is repeated a large number of times ( typically 1, 000 or 10, 000 times ), and for each of these bootstrap samples we compute its mean ( each of these are called bootstrap estimates ).
12. Because the bonus vote choices indicated by the survey respondents were hypothetical only, as a robustness check, the authors analyzed the bootstrap samples relying not only on the survey responses but also on three alternative plausible rules for casting the bonus vote.
13. Simply training many trees on a single training set would give strongly correlated trees ( or even the same tree many times, if the training algorithm is deterministic ); bootstrap sampling is a way of de-correlating the trees by showing them different training sets.