This is the most important part of any machine learning algorithm.
这是任何机器学习算法中最重要的部分。
But the new method is the first to predict the outcomes of court cases by automatically analysing case text using a machine learning algorithm.
但是，这一新途径是首次通过机器学习算法自动分析案件文本，来预测法庭判决结果。
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.
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。
The support vector machine based on statistical learning is a new type of machine learning algorithm, which has become the hot spot of academic study because of its excellent learning performance.
基于统计学习理论的支持向量机是一类新型的机器学习算法，由于它出色的学习性能，该技术已经成为当前学术界的研究热点。
In one embodiment, the machine learning algorithm generates a Bayesian network.
在一个实施例中，机器学习算法生成贝叶斯网络。
How do you know what machine learning algorithm to choose for your classification problem?
如何针对某个分类问题决定使用何种机器学习算法？
And a machine learning algorithm was proposed to handle the assignment of secondary accent.
而次重音的标注完全通过机器学习算法来进行。
A simple machine learning algorithm called naive Bayes can separate legitimate email from spam email.
一个简单的机器学习算法，朴素贝叶斯算法可以把正规邮件从垃圾邮件里面分离出来。
With limited samples, SVM has stronger ability of generalization in comparison with existing machine learning algorithm.
与现有的机器学习算法相比，在样本有限的情况下，支撑矢量机具有更强的分类推广能力。
Support vector machine is a new machine learning algorithm, based theoretically on statistic learning theory created by Vapnik.
为了系统地归纳统计学习理论与支持向量机的基本思想和算法，总结目前该领域的最新研究成果。
Based on the infrared feature database of the scene, a machine learning algorithm is applied to realize the IR scene real-time simulation.
为实现红外场景实时仿真，以场景的红外特性数据库为基础，将机器学习算法引入到仿真之中。
The scene is different, the detection accuracy is different, the user can put the safety cost is different, the machine learning algorithm is not the same.
场景不同，需要的检测精度不同，企业用户可以投入的安全成本不同，选用的机器学习算法也不相同。
The method of product feature extraction and analysis can be divided into supervised machine learning methods, semi-supervised machine learning algorithms and unsupervised machine learning algorithm.
产品评价对象的提取与分析的方法主要分为有监督的机器学习方法、半监督的机器学习算法、无监督的机器学习算法。
The method of product feature extraction and analysis can be divided into supervised machine learning methods, semi-supervised machine learning algorithms and unsupervised machine learning algorithm.
产品评价对象的提取与分析的方法主要分为有监督的机器学习方法、半监督的机器学习算法、无监督的机器学习算法。
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