袋排除法英文解释翻译、袋排除法的近义词、反义词、例句
英语翻译：
【医】 pocket elimination
分词翻译：
排除的英语翻译：
exclude; get rid of; debar; eliminate; obviate; remove【医】 deplete; depletion; elimination; evacuate; evacuation; exclusion
exhaustion; expel; pellate
【经】 dismiss; rule out
法的英语翻译：
dharma; divisor; follow; law; standard【医】 method
【经】 law
网络扩展解释
袋排除法
袋排除法是一种常用于机器学习领域的算法，也常被称为“基于袋的集成方法”或“随机森林算法”。
中文拼音
dài pái chú fǎ
英语解释翻译
Bagging, short for bootstrap aggregating, is a machine learning ensemble method that involves training several models on different subsets of the training data and combining their predictions through a majority vote.
英文读音
/ˈbæɡɪŋ/
英文用法
Bagging is used in machine learning to improve the stability and accuracy of a model by reducing overfitting and decreasing the variance of the predictions.
英文例句
One way to reduce the risk of overfitting in a decision tree model is to use bagging. For example, we can train multiple decision trees on random subsets of the training data and then combine their predictions to make a final prediction.
（在决策树模型中减少过度拟合的一种方法是使用袋排除法。例如，我们可以在训练数据的随机子集上训练多个决策树，然后将它们的预测组合起来进行最终预测。）
英文近义词
Bootstrap aggregating, ensemble learning, random forests
（自举聚集、集成学习、随机森林）
英文反义词
Boosting, error-correcting output coding, support vector machines
（提升、纠正输出编码、支持向量机）
英文单词常用度
bagging在计算机科学和机器学习领域非常常用，是一个基础性概念。