Description: 贝叶斯优化算法是一种新的演化算法，通过贝叶斯概率统计的知识来学习后代，可是使演化朝有利的方向前进，程序用C实现了贝叶斯优化算法。-Bayesian Optimization Algorithm is a new evolutionary algorithm, through Bayesian probability and statistics to learn the knowledge of future generations, but to enable the evolution towards a favorable direction, procedures C achieved a Bayesian Optimization Algorithm. Platform: |
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Author:龚文引 |
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Description: 贝叶斯优化算法是一种新的演化算法，通过贝叶斯概率统计的知识来学习后代，可是使演化朝有利的方向前进，程序用C实现了贝叶斯优化算法。-Bayesian Optimization Algorithm is a new evolutionary algorithm, through Bayesian probability and statistics to learn the knowledge of future generations, but to enable the evolution towards a favorable direction, procedures C achieved a Bayesian Optimization Algorithm. Platform: |
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Author:龚文引 |
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Description: 采用动量梯度下降算法训练BP网络，采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络-Gradient descent algorithm using momentum BP network training, using two training methods, namely, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to facilitate the training of BP network Platform: |
Size: 3072 |
Author:闫薇 |
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Description: 采用贝叶斯正则化算法提高bp网络的性能，即L-M优化算法-The use of Bayesian regularization algorithm to improve network performance bp, that is, LM optimization algorithm Platform: |
Size: 1024 |
Author:周妍 |
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Description: 采用贝叶斯正则化算法提高BP网络的推广能力。在本例中，将采用两种训练方法，即L-M优化算法（trainlm)和贝叶斯正则化算法（trainbr),用以训练BP网络，使其能够拟合某一附加有白噪声的正弦样本数据。-The use of Bayesian regularization algorithm for BP network to improve generalization ability. In this case, two types of training methods will be used, that is, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to facilitate the training of BP network to enable it to fit attached to a white noise of the sinusoidal sample data. Platform: |
Size: 1024 |
Author:qiulan |
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Description: 用L-M 优化算法与贝叶斯正则化算法训练同一个样本-By LM optimization algorithm with Bayesian regularization algorithm for training with a sample Platform: |
Size: 1024 |
Author:胡月 |
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Description: 动态贝叶斯网络结构学习算法，用来检验基于BOA的DBN结构寻优体系的合理性与可行性。环境matlab 6.1以上-Dynamic Bayesian network structure learning algorithm, the DBN used to test the structure-based optimization BOA system is reasonable and feasible. Environmental matlab 6.1 or above Platform: |
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Author:hsf |
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Description: 采用贝叶斯正则化算法（抑制过拟合）提高 BP 网络的推广能力，采用两种训练方法，
即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络；-Bayesian regularization algorithm (inhibition of over-fitting) to improve the generalization ability of BP network, using two training methods, that LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to train BP network Platform: |
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Author:liuwei |
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Description: 基于大坝温控的温度预报程序，采用了L-M优化算法和贝叶斯正则化算法，结果良好-Prediction based on the temperature of the dam temperature control program, using the LM optimization algorithm and the Bayesian regularization algorithm, good results Platform: |
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Author:杜晓帆 |
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Description: 《集体智慧编程》(programming collective intelligence building smart web 2.0 applications)以机器学习与计算统计为主题背景，专门讲述如何挖掘和分析web上的数据和资源，如何分析用户体验、市场营销、个人品味等诸多信息，并得出有用的结论，通过复杂的算法来从web网站获取、收集并分析用户的数据和反馈信息，以便创造新的用户价值和商业价值。全书内容翔实，包括协作过滤技术（实现关联产品推荐功能）、集群数据分析（在大规模数据集中发掘相似的数据子集）、搜索引擎核心技术（爬虫、索引、查询引擎、pagerank算法等）、搜索海量信息并进行分析统计得出结论的优化算法、贝叶斯过滤技术（垃圾邮件过滤、文本过滤）、用决策树技术实现预测和决策建模功能、社交网络的信息匹配技术、机器学习和人工智能应用等。-The collective wisdom of programming " (programming collective intelligence building smart web 2.0 applications) Machine Learning and Computational Statistics background data and resources devoted to mining and analysis on the web, how to analyze the user experience, marketing, personal tastes, and many other information and draw useful conclusions, through a complex algorithm obtained from the web site, the collection and analysis of user data and feedback information, in order to create a new user value and commercial value. The book is informative, including collaborative filtering technology (associated product recommendation function), cluster analysis (in large-scale data sets to explore similar data subset), the core technology of the search engine (reptiles, index, query engine, pagerank algorithm), search massive amounts of information and statistical analysis to draw conclusions optimization algorithm, Bayesian filtering technology (spam filtering, text filtering), decisi Platform: |
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Author:chenlei |
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Description: Traditional single particle reconstruction methods use either the Fourier or the delta function basis to represent the particle density map. We propose a more flexible algorithm that adaptively chooses the basis based on the data. Because the basis adapts to the data, the reconstruction resolution and signal-to-noise ratio (SNR) is improved compared to a reconstruction with a fixed basis. Moreover, the algorithm automatically masks the particle, thereby separating it from the background. This eliminates the need for ad-hoc filtering or masking in the refinement loop. The algorithm is formulated in a Bayesian maximum-a-posteriori framework and uses an efficient optimization algorithm for the maximization. Evaluations using simulated and actual cryogenic electron microscopy data show resolution and SNR improvements as well as the effective masking of particle from background Platform: |
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Author:无界 |
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Description: 采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正 -Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, namely LM optimization algorithm (trainlm) and Bayesian positive Platform: |
Size: 1024 |
Author:石勇 |
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Description: 采用贝叶斯正则化算法提高 BP 网络的推广能力。 在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。-Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, namely LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to train BP network so that it can fit a sine additional white noise sample data. Platform: |
Size: 1024 |
Author:张 |
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Description: 例1 采用动量梯度下降算法训练 BP 网络。
例2 采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。-Example 1 uses the momentum gradient descent algorithm to train the BP network.
Example 2 uses the Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, the LM optimization algorithm (trainlm) and the Bayesian regularization algorithm (trainbr), to train the BP network to fit a sine sample with white noise data.
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Author:李晓霜 |
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Description: LSTM 作为预测模型，使用贝叶斯优化算法来实现股票预测的功能(LSTM as a prediction model, uses Bayesian optimization algorithm to achieve the function of stock forecasting) Platform: |
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Author:某斌 |
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Search - bayesian optimization algorithm