Example problems are classification and regression.
这类问题包括分类和回归。
It has been well studied and widely applied to the classification and regression.
这种方法被深入地研究并广泛应用在诸如分类和回归问题上。
SVM can deal with nonlinear problems in classification and Regression easily by using kernel functions.
通过引入核函数，支持向量机可以很容易地实现非线性算法。
It also elaborates the ideas, counting steps and optimize algorithm of support vector classification and regression.
并且分别详尽的阐述了支持向量分类和支持向量回归的理论思想、计算步骤和优化算法。
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。
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。
This paper introduces the support vector classification and regression algorithms, which are applied to the structure damage identification.
介绍了支持向量机分类和回归算法，将其应用于梁结构的损伤诊断中。
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。
Discusses the classification and regression trees method, introduces its application in developing universities 'science research decision support system.
讨论了分类回归树方法，并介绍了它在开发高校科研决策支持系统中的应用。
SVM is the hot issue accompanying artificial neural network in machine learning. It involves any practical problems such as classification and regression estimation.
支持向量机是继神经网络后机器学习的热点研究技术，它主要应用于分类和回归问题中。
It is shown by the CART test that the classification and regression tree can satisfactorily accomplish the task of classification and prediction of the joint of welded spot.
CART测试结果表明，分类回归树可以较为满意地完成焊点接头强度的分类、预测任务。
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。
Support vector machine is a new technique of data mining, which is regarded as the best theory aimed at solving the problem of classification and regression of small sample pool at present.
支持向量机是数据挖掘的一项新技术，被认为是目前针对小样本的分类、回归等问题的最佳理论。
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。
Different support vector classification and regression predict models are constructed and applied to the solution of the customer classification, credit scoring, business prediction and so on.
通过建立不同类型的支持向量模型，解决了包括客户群体分类、信用评估、客户盈利能力预测等客户分析领域的众多复杂问题。
Data mining commonly involves a few standard tasks that include clustering, classification, regression, and associated rule learning.
数据挖掘通常涉及到一些标准的任务，包括聚集、分类、回归分析和关联性规则学习。
Like we did with the regression and classification model in the previous articles, we should next select the Classify TAB.
与我们在之前文章的回归和分类模型中所做的类似，我们接下来应该选择Classify选项卡。
So, at this point, this description should sound similar to both regression and classification.
从目前的这种描述看来，最近邻非常类似于回归和分类。
General regression neural network is proved with certain superiority in the ability of approaching, classification and learning speed.
广义回归神经网络在逼近能力、分类能力和学习速度方面具有较强优势。
Supervised learning with the use of regression and classification networks with sparse data sets will be explored.
也将在课程中以带有稀疏值理论的分类神经网路与回归的使用来探讨监督式学习。
A support vector regression method based on classification is presented to solve the nonlinear regression problem with unknown data distribution and mathematical model.
提出了一种基于分类技术的支持向量回归方法，解决数据分布未知、数学模型未知的非线性回归问题。
This article has also put forward the key procedure and method how to set up high-precision and high-efficiency classification model, regression model and clustering model with the system.
本文还重点提出了利用该系统建立精度好、效率高的分类、回归及聚类模型关键流程及方法。
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。
Parameters describing character of gray cast graphite morphology such as fractal dimension, roughness and regression coefficients were used to the classification.
用于描述石墨形态的特征由分形维、粗细参数和二维自回归系数共同组成。
The support vector machine (SVM) is a linear classification machine, it is used commonly in the pattern recognition and nonlinear regression.
支持向量机(SVM)是一种线性机器，广泛用于模式分类和非线性回归。
This case USES combined with fuzzy clustering and generalized regression neural network clustering algorithm for intrusion data classification.
本案例采用结合模糊聚类和广义神经网络回归的聚类算法对入侵数据进行分类。
For non-linear problem, the forecasting technique of pre-classification and later regression was proposed, based on the classification approach of Support Vector Machine (SVM).
针对非线性问题，提出了基于支持向量机分类基础的先分类、再回归的预测方法。
For non-linear problem, the forecasting technique of pre-classification and later regression was proposed, based on the classification approach of Support Vector Machine (SVM).
针对非线性问题，提出了基于支持向量机分类基础的先分类、再回归的预测方法。
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