"High dimensionality and small size samples" is widely encountered in many real world machine learning applications.
“高维度小样本”问题是模式识别应用中的主要障碍之一。
The introduction of machine learning allowed computers to tackle problems involving knowledge of the real world and make decisions that appear subjective.
机器学习的引入使得计算机能够处理一些涉及真实世界知识的问题，并且能够主观的做决定。
It is not only helpful for scientists to investigate machine learning and neural computing but also helpful for common engineers to solve real world problems using neural network techniques.
它不仅有助于科学家对机器学习和神经计算的深入研究，还有助于普通工程技术人员利用神经网络技术来解决真实世界中的问题。
Many real world problems deal with ordering objects instead of classifying objects, though most research in machine learning and data mining has been focused on the latter.
许多关于数据挖掘和机器学习的研究都集中于分类的研究，然而现实世界涉及到的不仅仅是分类问题，比如对象的排序问题。
Many real world problems deal with ordering objects instead of classifying objects, though most research in machine learning and data mining has been focused on the latter.
许多关于数据挖掘和机器学习的研究都集中于分类的研究，然而现实世界涉及到的不仅仅是分类问题，比如对象的排序问题。
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