可以采用一些机器学习方法来解决问题。
Several approaches to machine learning are used to solve problems.
支持向量机是一种新的机器学习方法。
支持向量机是一种新的机器学习方法。
Support vector machine is a new kind of machine learning method.
支持向量机(SVM)是一种新型的机器学习方法。
Support vector machine (SVM) is a new machine learning technique.
支持向量机是基于统计学习理论的一种新的机器学习方法。
Support Vector machine is a kind of new machine studying method, which is based on Statistical Learning Theory.
支持向量机是一种基于统计学习理论的新型机器学习方法。
Support vector machine (SVM) is a new learning machine based on the statistical learning theory.
所以我认为毫无疑问，机器学习方法会被越来越频繁地使用。
So I think there's no doubt many machine learning methods will get used more and more often.
自适应文本过滤中的机器学习方法包括模板学习和阈值学习。
Machine learning in adaptive text filtering includes profile learning and threshold learning.
支持向量机是一种具有超强边缘点捕捉能力的机器学习方法。
Support vector machine is a machine learning approach which has powerful ability to captive verge point.
论文将支持向量机的机器学习方法引入到医学图像的分类问题。
In this thesis, SVM as a new machine learning method is brought into medical image classification.
给出了基于解释的机器学习方法在电脑围棋死活知识学习中的应用。
Give out a explanation based machine learning method and how to apply it into extracting computer Go life-death knowledge.
实际上，在有历史数据可以积累的领域，机器学习方法均可发挥作用。
Actually, machine learning could demonstrate its power in any fields with historical data accumulation.
使用机器学习方法分析生物信息学中的复杂数据是目前重要的研究领域之一。
With the development of the bioinformatics, how to analyzes complex genomics data using machine learning approach has become an important research field.
为了提高胸癌诊断的识别精度，提出了应用机器学习方法建立胸癌诊断模型。
In order to improve the diagnosis accuracy, machine learning method was proposed to construct the breast cancer diagnosis model.
使用机器学习方法学习图像特征，自动建立图像类的模型成为一种有效的方法。
Using machine learning method to learn image features and to automatically construct models for image classes is a promising way.
摘要：支持向量机是一种新的机器学习方法，它具有良好的推广性和分类精确性。
Absrtact: Support vector machine is a kind of new machine learning method. This method has good generality capability and better classification accuracy.
摘要：介绍了构造性机器学习方法——覆盖算法在蛋白质二级结构预测中的应用。
Absrtact: Mainly introduces protein secondary structure prediction based on structural machine learning-covering algorithm.
基于统计学习理论中结构风险最小化原则的支持向量机是易于小样本的机器学习方法。
Support vector machine (SVM) based on the structural risk minimization of statistical learning theory is a method of machine learning for small sample set.
支持向量机是在统计学习理论基础上开发出来的一种新的、非常有效的机器学习方法。
SVM is a novel powerful machine learning method developed in the framework of Statistical Learning Theory (SLT).
本文详细比较了两种机器学习方法和两种统计翻译模型在英汉人名音译上的应用效果。
This paper applies to the problem of English-Chinese Name Transliteration both the machine learning and the mac.
针对不同长度术语的分布特性，结合机器学习方法从多角度提炼出术语结构的词法特征。
Based on the distribution features of terms with different length, some morphological rules of term structure are concluded by machine learning methods.
支持向量机是一种新的机器学习方法，它具有推广能力强、非线性和高维数等一系列优点。
Support Vector machine (SVM) is a new method of machine learning. It has some advantages such as generalization ability, nonlinear and high dimensions.
强化学习是一种重要的机器学习方法，然而在实际应用中，收敛速度缓慢是其主要不足之一。
Reinforcement learning is an important machine learning method. However, slow convergence has been one of main problem in practice.
由于在真核基因剪接位点的识别中引入了机器学习方法，剪接位点的识别率有了大幅度的提高。
Because of introducing the machine learning method in the recognition of splice sites of the eukaryotic DNA, the recognition rate of splice sites is largely heightened.
支持向量机是一种基于统计学习理论的机器学习方法，它解决了神经网络中存在的一系列问题。
Support Vector Machine(SVM) is a machine learning method based on Statistical Learning Theory. It can solve a series of issues of Neural Networks.
支持向量机是一种基于统计学习理论的新型机器学习方法，它可以被广泛地用于非线性系统建模。
Support vector machine (SVM) is a brand-new machine learning technique based on statistical learning theory. It is an ideal facility for modeling of various nonlinear systems.
支持向量机是一种基于统计学习理论的机器学习方法，该理论主要研究在有限样本下的学习问题。
Support vector machine is a kind of machine learning algorithm based on statistical learning theory which mainly researches the learning of limited number of samples.
实验结果表明，该识别系统在用于剪接位点的识别中，较常用的机器学习方法，获得了更高识别率。
The experimental results show that the HMM identification system acquires higher rate in the splice site identification than popular machine learning techniques.
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 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 have been developed for solving classification and regression problems.
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