第三，研究了学习分类器系统在多机器人学习中的应用。
Thirdly, Learning Classifier system is applied to multi-robot system.
该方法是从原始审计记录中归纳学习分类规则并利用这些规则建立入侵检测模型。
Classfication rules are inductively learned from audit records and used as intrusion detection models.
研究人工分类、机器学习分类的结合方法，提出基于“分类-使用-调整”逐步求精的分类方法。
Studying the combination of manual and machine learning classification, an classification approach for improving the precision based on "classification-use-adjustment is proposed".
文章简要介绍了人脸检测和支持向量机的概念，重点分析了常用的人脸检测方法和支持向量机如何应用于学习分类。
This part briefly introduces the concepts of human face detection and SVM, analyzes common face detection methods and how SVM be applied to learning and classifying.
在该演化算法中，采取训练正反类样本加权模板的方法来构造各个弱学习分类器，克服了常规的基于单一特征构造弱分类器的不足。
The algorithm used weighted templates to structure each weak learning classifier, which overcame the shortcoming of structuring classifier by using a single feature.
提出一种基于输入集分类函数的新的距离度量方法，它与前传回归的正交最小二乘法相结合，不仅可以学习分类超平面的参数，而且可以选择重要的输入节点。
Combining the new measure with the forward regression orthogonal least square (OLS), not only the parameters of the classification hyperplane, but also the important input nodes can be obtaind.
我们经常认为绘画需要天赋，但这种想法源于我们的错误分类——绘画主要是一种艺术形式，而不是一种学习工具。
We often think of drawing as something that takes inborn talent, but this kind of thinking stems from our misclassification of drawing as, primarily, an art form rather than a tool for learning.
他们学习了这些书，知道如何分类垃圾。
They have studied these books and known how to sort the rubbish.
这将在后面成为无监督学习上下文分类的一个例子。
This would be an example of unsupervised learning in a classification context.
不过这一类学习可能会非常强大，因为它假定没有事先分类的样本。
But this kind of learning can be powerful because it assumes no pre-discovered classification of examples.
另外一些常见的学习类型不是被设计用于为输入创建分类，而是作出决定；它们统称决策问题。
The other common type of learning is designed not to create classifications of inputs, but to make decisions; these are called decision problems.
数字识别再一次成为分类学习的常见样本。
Digit recognition, once again, is a common example of classification learning.
请注意这里提到的一个问题：在分类问题中，学习算法的目标是把给定输入中的错误最小化。
Notice something important here: in the classification problem, the goal of the learning algorithm is to minimize the error with respect to the given inputs.
虽然我没有关于童年的太多记忆，但是我清晰的记得我在小学的时候学习动物分类的事情。
Although I don't have a ton of memories from my childhood, I distinctly remember being in elementary school and learning about animal classification.
如果通过算法作出的决定需要输入别的地方，这时分类学习是必要的。
Classification learning is often necessary when the decisions made by the algorithm will be required as input somewhere else.
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。
Data mining commonly involves a few standard tasks that include clustering, classification, regression, and associated rule learning.
监管学习的常见例子包括将电子邮件消息分类为垃圾邮件，根据类别标记网页，以及识别手写输入。
Common examples of supervised learning include classifying E-mail messages as spam, labeling Web pages according to their genre, and recognizing handwriting.
患者安全主要概念的标准化分类，是分享全世界卫生保健系统学习的关键。
A standardized classification for key patient safety concepts is vital to share learning across health-care systems all over the world.
监督学习是最常见的分类问题，因为目标往往是让计算机去学习我们已经创建好的分类系统。
Supervised learning is fairly common in classification problems because the goal is often to get the computer to learn a classification system that we have created.
在无指导的情况下，将上述数据库的图像显示在还未受训的回旋网眼前，它能学习识别70%以上的分类。
When a ConvNet with unsupervised pre-training is shown the images from this database it can learn to recognise the categories more than 70% of the time.
对无监督学习来说这个目标很难实现，因为缺乏事先确定的分类。
In unsupervised learning, the goal is harder because there are no pre-determined categorizations.
美国加州斯坦福大学的一个研究团队利用计算机学习软件分类整理了由脑部扫描所得的数据，从而对人们处于疼痛的时刻进行了检测。
A team at Stanford University in California used computer learning software to sort through data generated by brain scans and detect when people were in pain.
例如，某些基本的神经网络，它们的感知器只倾向于学习线形函数(通过划一条线可以把函数输入解析到分类系统中)。
For instance, a certain kind of basic neural network, the perceptron, is biased to learning only linear functions (functions with inputs that can be separated into classifications by drawing a line).
垃圾邮件过滤程序使用基于人工智能的学习和分类技术，每天从所有邮件里鉴别出2000亿封垃圾邮件中的99.9%。
Spam filtering programs using A.I. learning and classification techniques correctly identify over 99.9% of the 200 billion spam e-mails sent each day.
Classification：该学习对象是否符合特定的分类系统。
Annotation.Classification: Where this learning object falls within a particular classification system.
JustCreativeDesign的《排版分类》对想学习印刷设计艺术的人员来说是非常优秀的教育资源。无论排版是不是你的专长，这本书都值的一读。
Just Creative design's Type Classification eBook is a fantastic educational resource for those wish to learn more about the fine art of typographical design.
LanguageExchange Net work：克雷格列表也可以用在语言学习上；该站点拥有超简单的语言交流分类列表。
Language exchange Network: Think Craigslist for language learning; this site has super-simple language exchange classified listings.
同样，对于机器学习算法，一个通常的问题是过适合(原文为over -fitting，译者注)数据，以及主要记忆训练集，而不是学习过多的一般分类技术。
Similarly, with machine learning algorithms, a common problem is over-fitting the data and essentially memorizing the training set rather than learning a more general classification technique.
通过artima Weblogs Forum深入学习Python中的类型和分类。
Learn more about types and typing in Python at the artima Weblogs Forum.
更一般地说，对于那些有用的分类系统，和容易判断的分类系统，分类学习都适用。
More generally, classification learning is appropriate for any problem where deducing a classification is useful and the classification is easy to determine.
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