unsupervised learning造句
例句与造句
- The former belongs to supervised learning and the latter belongs to unsupervised learning
它们分属于有监督学习与无监督学习。 - The distinct difference between supervised learning and unsupervised learning lies in whether the example consists of the pre - processed output value
这两种方法最大的区别就在于学习样本是否包含有预先规定好的输出值。 - Decision theory , statistical classification , maximum likelihood and bayesian estimation , non - parametric methods , unsupervised learning and clustering
决策理论，统计分类，最大似然和贝叶斯估计，非参数方法，非监督的学习与聚类。 - Due to its unsupervised learning ability , clustering has been widely used in numerous applications , such as pattern recognition , image processing , market research and so on
聚类具有无监督学习能力,被广泛应用于多个领域中,如模式识别、数据分析、图像处理以及市场调研等。 - Both theories are combined to classify the documents by unsupervised learning and discuss the method in which new rules , applied to new unclassified documents , can be formed after classifying the training documents
本文利用文档聚类和粗糙集约简相结合的方法，对训练文档进行分类，形成规则后对新加入的未分类文档进行归类。 - It's difficult to find unsupervised learning in a sentence. 用unsupervised learning造句挺难的
- 3 ) semantic classification model based som network we use the classification model to combines attributes within a database . this is done using an unsupervised learning algorithm . the output is used as training data for the next stage
3 )基于som网络的语义分类模型设计建立som网络模型，将元数据特征向量进行分类，形成bp网络的目标向量，用于匹配规则的提取。 - The supervised and unsupervised learning diagnosis methods are discussed and several improvements have been presented in the learning algorithms . the simulation results show that the proposed method can perforfti correct diagtioals iii the linear analog circuits with tolerances
本文对模拟故障诊断的有监督学习和无监督学习方法分别进行了研究，通过对实现过程的分析，对经典的学习算法进行深入研究，并提出若干改进。 - Refer to chinese automatic word segmentation based on statistics , this paper imports the mechanism of open learning , and uses the method of supervised and unsupervised learning . the word segmentation model includes credibility revising and partial tri - gram information
本文在基于统计的汉语自动分词的基础上，引入开放学习机制，通过有监督和无监督相结合的学习方法，建立包含可信度修正和部分三元语法信息的多元分词模型。 - Based on unsupervised learning , sparse coding is suitable to describe images with non - gaussian distribution and can get rid of the high order redundancy among the image pixels . since the basis function of sparse coding has build - in clustering property , it increases the inter - class variations of the features
稀疏编码是一种基于非监督学习的算法，它适合描述具有非高斯分布的数据对象，能够有效地消除图像象素点之间的冗余，并具有内在的聚类特性。 - 1 , q 3 , and at last prove the exisitence of ( q , m + n , n , m ) resilient functions when n > q ? 1 . intelligentized ids methods , which can make the system more adaptability and self - studying , are important research directions of ids so far . in order to make the ids systems have better identifying ability and efficiency against new intrusions , we propose the intrusion feature extra - ction algorithm based on ikpca by studying the different kinds of intrusion detection feature extraction algorithm based on unsupervised learning , and then theoretically analysis the conver - gence of the algorithm . in addition , we validate the validity of the algorithm by means of experim - ents ; at the same time , through studying ica and neural networks , we propose fastica - nn ids , and then test the kddcup99 10 % date set to make comparison of kpca 、 ikpca and fastica algorithms in intrusion detection advantages and disadvantages
为了使入侵检测系统对新的入侵行为有更好的识别能力和识别效率,本文在研究了各种基于无监督学习的入侵检测特征提取方法的基础上,提出了基于增量核主成份分析( ikpca )的入侵检测特征提取方法,并对该方法进行了收敛性分析,同时结合仿真试验对其正确性进行了验证;另外,本文通过研究独立成份分析和神经网络,提出了基于快速独立成份分析和神经网络的入侵检测方法( fastica - nnids ) ,并通过对kddcup99的10 %数据集的检测比较了核主成份分析( kpca ) 、增量核主成份分析( ikpca )和快速独立成份分析( fastica )在入侵检测特征提取方面的优缺点。
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