What is the translation of " 随机森林 " in English?

• random forest
• random forests

Examples of using 随机森林 in Chinese and their translations into English

在随机森林方法中，创建大量的决策树。
In the random forest approach, a large number of decision trees are created.

棵随机森林.
A Random Forest.

随机森林是由许多决策树构成的模型。
The random forest is a model made up of many decision trees.

随机森林包含多颗决策树。
A Random Forest consists of a certain number of decision trees.

具体来说，我们将详细研究随机森林和AdaBoost算法。
In particular, we will study the Random Forest and AdaBoost algorithms in detail.

决策树、随机森林、梯度增加等方法被广泛用于各种数据科学问题。
Methods like decision trees, random forest, gradient boosting are being popularly used in all kinds of data science problems.

随机森林天然可用来对回归或分类问题中变量的重要性进行排序。
Random forests can be used to rank the importance of variables in a regression or classification problem in a natural way.

决策树、随机森林、gradientboosting等方法被广泛用于各种数据学科问题中。
Methods like decision trees, random forest, gradient boosting are being popularly used in all kinds of data science problems.

例如：你可能会很快了解随机森林如何运作，但了解其背后的逻辑需要额外的努力。
For example: You might quickly understand how does a random forest work, but understanding the logic behind it's working would require extra efforts.

基于树的算法：决策树、随机森林和提升树等基于树的算法用于解决分类和回归问题。
Tree-Based algorithms: Tree-based algorithms such as decision trees, Random Forests, and Boosted trees are used to solve both classification and regression problems.

在这篇文章中，您将学习随机森林算法如何工作以及其他几个重要的事情。
In this post, you are going to learn, how the random forest algorithm works and several other important things about it.

在随机森林中，集成的每一棵树都是从训练集中用替换（例如，引导样本）绘制样本构建的。
In random forests, each tree in the ensemble is built from a sample drawn with replacement(i.e. a bootstrap sample) from the training set.

相比之下，随机森林模型正确预测了约64%的过早死亡，而考克斯模型只确定了约44%。
By comparison, the random forest model correctly predicted about 64 percent of premature deaths, while the Cox model identified only about 44 percent.

由于深度学习如此受欢迎，我们将研究随机森林、AdaBoost和深度学习神经网络之间的一些有趣的共同点。
Deep learning is so popular these days, we will study some interesting commonalities between random forests, AdaBoost, and deep learning neural networks.

随机森林模型也成功地应用于稀疏训练集和无样本预测，这表明了其在促进合成方法采用方面的价值。
The random forest model was also successfully applied to sparse training sets and out-of-sample prediction, suggesting its value in facilitating adoption of synthetic methodology.

像随机森林这种模型可解释性稍差，更适合“机器学习”的描述，而深度学习等方法则难以解释。
Models like random forests are less interpretable, More suitable“ machine learning” Description, But deep learning is hard to explain.

它由k-NN、随机森林和朴素贝叶斯基础分类器组成，它的预测结果由作为元分类器的Logistic回归组合。
It consists of k-NN, Random Forest, and Naive Bayes base classifiers whose predictions are combined by Logistic Regression as a meta-classifier.

在随机森林中，集成中的每棵树都是由从训练集中抽取的样本（即bootstrap样本）构建的。
In random forests, each tree in the ensemble is built from a sample drawn with replacement(i.e. a bootstrap sample) from the training set.

研究小组使用机器学习-特别是随机森林技术-来确定哪些标记物可用于诊断创伤后应激障碍。
The research team used machine learning- specifically, the random forest technique- to determine which markers would be useful in diagnosing PTSD.

为了估计真正的f,我们会使用线性回归或者随机森林等不同的方法。
To estimate the true\(f\), we use different methods, like linear regression or random forests.

定义随机森林建立多个决策树并将它们合并在一起以获得更准确和稳定的预测。
To say it in simple words: Random forest builds multiple decision trees and merges them together to get a more accurate and stable prediction.

我们注意到，产业数据科学家们更倾向于使用回归、可视化、统计、随机森林和时间序列。
We note that Industry Data Scientists are more likely to use Regression, Visualization, Statistics, Random Forests, and Time Series.

这里，基于具体的机器学习问题，我们要应用有效的算法，如回归，决策树，随机森林等。
Here, based on our specific machine learning problems, we apply useful algorithms like regressions, decision trees, random forests, etc.

决策树的自然扩展就是随机森林，它把成千上万的树合并到一起来获得更强的预测能力，代价是牺牲了解释能力。
Their natural extension is the Random Forest, which combines hundreds or thousands of trees to gain predictive power at the expense of interpretability.

随机森林算法将随机抽取一个包含100个观测值的样本和5个随机选择的初始变量，构建一个CART模型，然后执行。
The Random Forest algorithm will take a random sample of 100 observations and five randomly chosen initial variables to build a CART model to work through.

Scikit-learn配备了各种ML模型，包括线性和逻辑回归器、SVM分类器和随机森林。
SciKit-Learn is equipped with a variety of ML models including linear and logistic regressors, SVM classifiers, and random forests.

集成建模的最佳示例是随机森林，其中许多决策树用于预测结果。
A best example of ensemble modelling is the random forest trees where many decision trees are used for predicting the results.

我们注意到产业界数据科学家更倾向使用回归算法、可视化、统计算法、随机森林算法和时间序列。
We note that Industry Data Scientists are more likely to use Regression, Visualization, Statistics, Random Forests, and Time Series.

随机森林算法可被用于很多不同领域，如银行，股票市场，医药和电子商务。
The random forest algorithm is used in a lot of different fields, like Banking, Stock Market, Medicine and E-Commerce.

在机器学习中，我们经常使用“黑盒子”方法-[也叫做分类算法]、随机森林或更深入的学习方法。
In machine learning, we often use“black-box” methods-[classification algorithms called] random forests, or deeper learning approaches.