Support vector machines (SVM) are a kind of novel machine learning methods, based on statistical learning theory, which have been developed for solving classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Support vector machines (SVM) are a kind of novel machine learning methods based on statistical learning theory, which has been developed to solve classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Bayesian methods are those that are explicitly apply Bayes' Theorem for problems such as classification and regression.
贝叶斯方法是那些明确地在分类和回归问题中应用贝叶斯定理的算法。
The classification of cultivation measures for spring maize was studied with the principal factor analysis and regression methods.
应用因子分析和回归方法对春玉米高产农艺措施进行了数量分类与寻优。
Kernal methods and support Vector Machines (SVMs) are related to Gaussian processes and can also be used in classification and regression problems.
内核方法和支持向量机(SVMs)与高斯过程相关并应用于分类和回归问题。
Decision trees and their ensembles are popular methods for the machine learning tasks of classification and regression.
决策树和决策树的组合，是解决分类问题和回归问题比较流行的一类算法。
Decision trees and their ensembles are popular methods for the machine learning tasks of classification and regression.
决策树和决策树的组合，是解决分类问题和回归问题比较流行的一类算法。
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