支持向量机(Support Vector Machine, SVM)是一类按监督学习(supervised learning)方式对数据进行二元分类的广义线性分类器(generalized linear classifier),其决策边界是对学习样本求解的最大边距超平面(maximum-margin hyperplane)。 详情可查看我的主页,有具体介绍支持向量机SVM的文章。 10 Dimensional Reduction:降维算法 ...
二、unsupervised learning 非监督式学习 非监督式学习不使用labeled data,没有期望的target,所以它适用于数据量很大或者很复杂的情况。适合解决以下两种问题:1、降维(dimension reduction)2、聚群(clustering) 三、deep learning and reinforcement learning 深度学习 深度学习使用更复杂的算法处理复杂的问题,例如图片分类、...
常见算法有 Isolation Forest, One-class SVM等 降维Dimension Reduction: 常见算法有 PCA, Kernel PCA, t-SNE 等 (3) 半监督学习 Semi-supervised Learning 当机器学习使用的训练集数据部分有标注时(通常是大部分无标注,而只有小部分有标注),我们称之为半监督学习。 大多数半监督学习的算法是无监督学习和有监督...
Deep learning neural networks can be constructed to perform dimensionality reduction. A popular approach is called autoencoders. This involves framing a self-supervised learning problem where a model must reproduce the input correctly. For more on self-supervised learning, see the tutorial: 14 Differe...
O.A. DeMasi, J.C. Meza, and D.H. Bailey. Dimension reduction using rule ensemble machine learning methods: A numerical study of three ensemble methods. 2011. http://crd.lbl.gov/~dhbailey/ dhbpapers/Ensemble_TechReport.pdf.O. DeMasi, J. Meza, and D. Bailey. Dimension reduction using...
机器学习(Machine Learning)&深度学习(Deep Learning)资料(Chapter 1) 《Brief History of Machine Learning》 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机、神经网络、决策树、SVM、Adaboost到随机
if you are using dimensionality reduction as a preprocessing step before another Machine Learning algorithm (e.g., a Random Forest classifier), then you can simply measure the performance of that second algorithm; if dimensionality reduction did not lose too much information, then the algorithm shou...
《Brief History of Machine Learning》 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机、神经网络、决策树、SVM、Adaboost到随机森林、Deep Learning. 《Deep Learning in Neural Networks: An Overview》 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最新版本《神经网络与深度学习综述》本综述的特点...
In deep learning technologies, the introduction of the multilinear subspace learning algorithm has led to the proposition of a method of novel fault diagnosis. With the help of multilinear principal com-ponent analysis, a reduction in the multi-channel data dimension is performed. The tensor ...
1.2 Machine learning Machine learning is a topic of artificial intelligence where it is possible to elaborate algorithms to teach a particular machine to perform a task. It is necessary to have a dataset, and from that data, explore the correlation between them, discovering patterns and applying ...