回归问题 in English translation

• a regression problem

Examples of using 回归问题 in Chinese and their translations into English

例如，对无人机、机器人、自动驾驶汽车、分子回归问题、全球天气和气候模型的全方位视觉处理问题。
Examples include omnidirectional vision for drones, robots, and autonomous cars, molecular regression problems, and global weather and climate modelling.

我们以讨论回归问题开始，现在我们只考虑可以取任何实数值的一元目标变量的情形。
We start by discussing regression problems, and for the moment we consider a single target variable t that can take any real value.

BayesianRidge类会估计一个求解回归问题的概率模型(probabilisticmodel)。
BayesianRidge estimates a probabilistic model of the regression problem as described above.

我们现在将支持向量机推广到回归问题，同时保持它的稀疏性。
We now extend support vector machines to regression problems while at the same time preserving the property of sparseness.

回归问题：其中要预测的变量是数字的（例如房屋的价格）；.
Regression problems, where the variable to predict is numerical(e.g., the price of a house).

它确实在分类方面做得很好，但不如回归问题好，因为它不提供精确的连续自然预测。
It surely does a good job at classification but not as good as for regression problem as it does not give precise continuous nature predictions.

回到多项式回归问题，我们可以画出模型证据与多项式阶数之间的关系，如图3.14所示。
Returning to the polynomial regression problem, we can plot the model evidence against the order of the polynomial, as shown in Figure 3.14.

平均法可用于在回归问题中进行预测或在计算分类问题的概率时使用。
Averaging can be used for making predictions in regression problems or while calculating probabilities for classification problems..

它通常用于线性和非线性回归问题，在摄影测量计算机视觉领域尤其流行。
It is typically used for linear and non-linear regression problems and is especially popular in the fields of photogrammetric computer vision.

这种算法主要解决线性或非线性回归问题，在计算机视觉摄影测量领域尤为流行。
It is typically used for linear and non-linear regression problems and is especially popular in the fields of photogrammetric computer vision.

回归问题：你可以将本实现应用到一些回归问题（预测基于数值的属性）。
Regression: You could adapt the implementation to work for regression problems(predicting a real-valued attribute).

该数据集能帮你完成回归问题，它包括515345个观察值和90个变量。
It is a regression problem which consists 515345 observations and 90 variables.

决策树也可以应用于回归问题，使用sklearn的DecisionTreeRegressor类。
Decision trees can also be applied to regression problems, using the DecisionTreeRegressor class.

深度学习技术在解决众所周知很困难的分类和回归问题方面取得了成功，这使得该技术迅速应用于解决现实问题。
The success of deep learning techniques in solving notoriously difficult classification and regression problems has resulted in their rapid adoption in solving real-world problems..

对于一个正常的分类或者回归问题，我们通过交叉验证来处理。
For a normal classification or regression problem we would do this using cross validation.

由输出数据分类：如果模型的输出是一个数值，这属于回归问题。
Categorize by output: If the output of the model is a number, it's a regression problem.

SVM是一种有监督的机器学习算法，可用于分类或回归问题。
SVM is a supervised machine learning algorithm which can be used for classification or regression problems.

BayesianRidgeestimates(贝叶斯岭方差估计)如上所述的回归问题的概率模型。
BayesianRidge estimates a probabilistic model of the regression problem as described above.

大多数人倾向于将两种常见的线性或逻辑回归中的任何一种应用于几乎每个回归问题。
Most people tend to apply either of the two common ones, linear or logistic regression, to almost every regression problem.

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.