Classification Learning is the important content in Machine Learning.
分类学习是机器学习重要的研究内容。
Digit recognition, once again, is a common example of classification learning.
数字识别再一次成为分类学习的常见样本。
Classification learning is often necessary when the decisions made by the algorithm will be required as input somewhere else.
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。
Each software tutorials with basic tutorials, advanced tutorials, case tutorials, tips, easy exercise to classification learning.
每个软件教程都以基础教程、高级教程、实例教程、技巧、练习来分类方便您学习。
During the preprocessing of classification, it is important to select feature subset effectively, in order to classification learning and predicting.
在分类挖掘的预处理过程中，重要的是如何选择最有效的特征子集，以便于分类学习与预测。
More generally, classification learning is appropriate for any problem where deducing a classification is useful and the classification is easy to determine.
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。
Category learning is increasingly concerned in the last decade. There are two forms of category learning, classification learning and inference learning.
类别学习在近十年受到研究者的极大关注，类别学习有两种形式，分别为分类学习和推理学习。
This would be an example of unsupervised learning in a classification context.
这将在后面成为无监督学习上下文分类的一个例子。
But this kind of learning can be powerful because it assumes no pre-discovered classification of examples.
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。
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.
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。
Although I don't have a ton of memories from my childhood, I distinctly remember being in elementary school and learning about animal classification.
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。
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。
A standardized classification for key patient safety concepts is vital to share learning across health-care systems all over the world.
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。
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.
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。
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.
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%。
Annotation.Classification: Where this learning object falls within a particular classification system.
Classification：该学习对象是否符合特定的分类系统。
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.
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。
The proficiency in classification and selection of Sol-fa and the mastery over training methods and steps of intonation are fundamental prerequisites for learning solfeggio.
对唱名法的分类与选择、音准的训练方法与步骤等内容的熟练掌握是学习视唱练耳的基本前提。
Effective dimensionality reduction could make the learning task more efficient and more accurate in text classification.
在文本分类中，有效的维数约简可以提高学习任务的效率和分类性能。
In this thesis, SVM as a new machine learning method is brought into medical image classification.
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。
SVM for text classification - tutorial on machine learning? How do I get started?
SVM文本分类的机器学习教程？我如何开始？
This dissertation focuses on efficient exact inference on belief networks, learning belief networks from data, and classification using belief networks.
本论文详细研究了信度网精确推理、信度网学习和信度网分类有关内容。
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？
VC dimension plays a central role in the Statistical Learning Theory especially for classification problems.
在统计学习理论中，尤其对于分类问题，VC维扮演着中心作用。
Classification by machine learning is an important technique to predict gene functions.
应用机器学习进行分类是基因功能预测的一种重要手段。
And classification is the basis of the common Machine Learning problem.
分类是许多机器学习问题解决的基础。
There are eight features used to form the feature vector for each sentence, and the summarizer is gained by machine learning algorithms, so automatic summarization is changed into classification task.
用这些特征构成句子向量表示，并用机器学习的方法对其进行训练得到器，从而把自动文摘转换为分类问题。
The quick diagnosis means quick learning and classification.
快速诊断要求快速学习和快速分类。
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。
The early study on language learning strategies was mainly concerned with identifying and describing language learning strategies and their classification.
早期的研究主要侧重于归纳、描述学习策略以及对其进行分类。
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