提出一种并行的决策树学习方法。
A new parallel learning method of the decision tree is proposed in this paper.
决策树学习是应用最广泛的归纳推理算法之一。
Decision tree learning is one of the widely used and practical methods for inductive inference.
决策树简化是决策树学习算法中的一个重要分支。
Decision tree simplification is a significant branch in the study of decision-tree learning algorithms.
ID 3算法是最基本的决策树学习算法，有很广的应用。
ID3 algorithm is the most basic algorithm in the decision tree learning, and has a wide application.
介绍了归纳学习中的决策树学习算法如id3、C4.5和特征子集选择问题。
And it introduces some algorithms of decision tree learning such as ID3, C4.5 and feature subset selection of Inductive learning.
通过对原有决策树学习算法的研究，提出了以分类准确度为基础的属性选择算法；
We bring forward the newly attribute chosen algorithm based on classified certain degree of condition attributes for decision attribute.
决策树学习策略广泛应用于模式识别和机器学习等领域，用来解决与分类相关的问题。
Decision tree learning strategy have long been popular in pattern recognition, machine learning, and other disciplines for solving problems concerned with the classification.
当我们在后面具体提及决策树时，将会进一步讨论验证集，因为它通常是决策树学习的最优选择。
We'll discuss validation sets when we look at decision trees because they are a common optimization for decision tree learning.
这种学习可以使用神经网络或者支持向量机，不过用决策树也可以实现类似的功能。
This sort of learning could take place with neural networks or support vector machines, but another approach is to use decision trees.
监督学习是训练神经网络和决策树的最常见技术。
Supervised learning is the most common technique for training neural networks and decision trees.
这种类型的学习通常交给神经网络来完成，虽然很难想象，但用决策树来完成这类问题也很简单。
This type of learning could probably be carried out with neural networks, though it is hard to imagine that the problem is simple enough for decision trees.
也许用决策树来学习如何在丛林中勘查是非常愚蠢的，但用它们在餐馆中选取食物却非常合适。
It might be very silly to use decision trees for learning how to actually explore a jungle but very reasonable to use them for picking food at a restaurant.
通过对决策树分类算法的比较，本文采用C4.5决策树算法实现自学习模块。
Comparing with Decision Tree algorithms, this system chooses the C4.5 to realize the self-learning module.
通过对训练数据的学习，生成用于轨道故障判决的决策树(或者规则)。
The decision tree (or rules) used for rail deformation detection was generated by learning the train data.
该文根据自相关函数与谱密度函数之间的对应关系，提出了一种新的基于自相关函数的决策树归纳学习算法。
According to the relationship between auto correlation function and its spectral density, a new type of decision tree method based on signal analysis theory is proposed in this paper.
在这个过程中，应用了决策树归纳学习的优化原则，使得生成的决策树能最简洁、准确地描述神经网络学到的知识。
In the process of constructing tree, three optimization principles are adopted to concisely and accurately describe the knowledge that the networks have learned.
基于ID 3算法的决策树归纳学习是归纳学习的一个重要分支，可用于知识的自动获取过程。
Induction learning of decision tree based on ID3 algorithm is an important branch of inductive learning now, which can be used to automatic acquisition of knowledge.
树的简化是决策树归纳学习中关键的部分。
Simplifying trees is the key part of decision tree induction learning.
决策树的学习算法，比如id3算法，选用最小信息熵作为启发式信息。
Minimum entropy is chosen as a heuristic strategy in decision tree (DT) learning algorithm such as ID3.
接下来讨论了规则的表示问题：决策树的获取方法和IF -THEN规则表达法，新例对规则的学习等问题。
We put them into IF-THEN and Decision Trees by some methods. We also discuss how to learn in rule sets.
运用云神经网络学习变量间的云映射关系，从中生成云决策树。
It adopts cloud neural network to study the cloud mapping relationship between variables, so as to generate cloud decision tree.
提出了一种融合无监督和监督两种学习策略生成多分类决策树的方法。
In this paper, a new method which combines unsupervised and supervised learning strategy is put forward to construct the multi classification decision tree.
系统采用决策树方法作为数据挖掘方法的基本算法，采用训练与学习相结合实现土地定级估价。
For land grading and evaluating, training and learning method is adopted and the integration of them implemented.
决策树是归纳学习和数据挖掘的重要方法，通常用来形成分类器和预测模型。
Decision tree is an important method in induction learning as well as in data mining, which can be used to form classification and predictive model.
决策树方法是发现概念描述空间的一种特别有效的方法，是实例学习中具有代表性的学习方法，专门用于处理大量对象。
The decision tree method is the effective method of detecting for concept describing space and the representative learning way in exampling learning of which specially dispose mass object.
实验结果表明，系统所使用的轮廓线向量图像特征也能够较有效地应用于图像方向分类，而机器学习则能够有效地为之建立决策树分类模型。
Using teacher images and machine learning method, an image direction classification model is built as a decision tree. Test results argued the validity of this method.
现在我已经做了对的监督和无监督学习算法，如决策树，一些基本的阅读聚类，神经网络等。
Now I have done some basic reading on supervised and unsupervised learning algorithms such as decision trees, clustering, neural networks... etc.
决策树是机器学习和数据挖掘领域中一种基本的学习方法。
Decision tree is a basic learning method in machine learning and data mining.
为了提高歼击机故障诊断的准确性与实时性，提出一种基于决策树型组合策略的多重核学习支持向量机诊断方法。
Based on decision tree combined strategy and multiple kernel learning support vector machines, a new fault diagnosis method is proposed to improve the precision and speed of fighter fault diagnosis.
为了提高歼击机故障诊断的准确性与实时性，提出一种基于决策树型组合策略的多重核学习支持向量机诊断方法。
Based on decision tree combined strategy and multiple kernel learning support vector machines, a new fault diagnosis method is proposed to improve the precision and speed of fighter fault diagnosis.
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