搜索资源列表
DBN
- 深度信念神经网络应用程序,部分数据及仿真例程(Deep belief neural network application, simulation routine)
dbn-master
- 度信念网络是一个概率生成模型,与传统的判别模型的神经网络相对,生成模型是建立一个观察数据和标签之间的联合分布,对P(Observation|Label)和 P(Label|Observation)都做了评估,而判别模型仅仅而已评估了后者,也就是P(Label|Observation)。(The degree belief network is a probability generation model. Compared with the neural network of the tradi
DBN
- 深度信念网络,神经网络的一种。既可以用于非监督学习,类似于一个自编码机;也可以用于监督学习,作为分类器来使用。(Deep belief network, a kind of neural network. It can be used for unsupervised learning, similar to a self-coding machine, or supervised learning, as a classifier.)
Deep learning_CNN DBN RBM
- 运用深度学习模型实现图像的分类,主要包括卷积神经网络CNN和深信度网络DBN(Classification of images using deep learning model includes convolutional neural network CNN and belief network DBN.)
StructureLearningLibraries-master
- 贝叶斯网络又称信度网络,是Bayes方法的扩展,是目前不确定知识表达和推理领域最有效的理论模型之一。从1988年由Pearl提出后,已经成为近几年来研究的热点.。一个贝叶斯网络是一个有向无环图(Directed Acyclic Graph,DAG),由代表变量结点及连接这些结点有向边构成(Bayesian network, also known as belief network, is an extension of Bayes method and one of the most effec
DBN
- 深度信念网络程序详解,可以实现数据回归和分类,自动提取关键成分。(Detailed explanation of deep belief network program can realize data regression and classification, and automatically extract key components.)