搜索资源列表
BVAR
- 贝叶斯的自回归程序,很棒,比一般的VA要强大的多
BCS_fast_rvm
- 该代码实现的是压缩感知理论中的信号恢复问题。将压缩感知理论中的信号恢复问题转化为带参数约束的回归问题,从而利用贝叶斯理论实现参数估计,从而得到高效的重建稀疏信号。-The code to achieve the signal recovery problems in the theory of compressed sensing. Recovery issues into regression problems with parameter constraints will signal co
Data_Mining_SQL_2008
- 这是《数据挖掘原理与应用—SQL Server 2008数据库》的随书SQL语句、源代码和Excel范例文件,基于DMX,代码主要包括对SQL Server 2008和Excel 2007中已经集成好的数据挖掘算法的应用, 如贝叶斯聚类、决策树、时序、聚类、序列聚类、关联规则、神经网络、逻辑回归、OLAP立方体的等算法,具有极高的使用价值。-This is the " Principles and Applications of data mining-SQL Server 2008 d
webcat
- 这是一个100 %纯Java库,您可以使用适用于N元 分析技术的过程分为文本文件。 该计划包括几个不同的分类算法, namelly 支持向量机,贝叶斯Logistic回归,神经网络分类和文本压缩 算法。如支持向量机和贝叶斯Logistic回归,一个 “一对一” 用于多类分类。更详细的说明这些学习算法和可用的选项,请提供的javadocs 。-It is a 100 pure Java library that you can use to apply N-Gr
BMDCP
- 突变分为如下主要的几种:均值突变(最常见)、方差突变、线性回归突变(也称趋势突变)、概率突变、空间型突变、谱突变、模型参数突变,等等。贝叶斯突变检测属于概率突变检测方法,其特点是能给出突变点的概率分布图。-Mutations are divided into the following main categories: the mean mutation (the most common), variance mutation, linear regression mutation (also
sf1847
- 数据挖掘建模工具,轻易实现BP神经网络、RBF神经网络、灰色系统、决策树、决策表、贝叶斯、懒惰算法、支持向量机、K均值聚类、Apriori关联规则、HotSpot关联规则、回归分析、指数平滑、季节移动平均及组合等算法建模。-Data mining modeling tools, easy to achieve BP neural network, RBF neural network, gray system, decision tree, decision table, Bayesian, l
BVAR_Gibbs
- 贝叶斯分析,比较复杂的自回归分析。VAR模型,注意比AR要先进的多!-Bayesian estimation, prediction and impulse response analysis in VAR models using the Gibbs sampler.
Sparse-Bayesian-Learning-and-rvm
- 稀疏贝叶斯学习和相关向量回归,大家可以看一下,人工智能中的应用-Relevance vector machine, new applications in the field of artificial intelligence, I hope you look at...
barsP_matlab
- 贝叶斯自适应回归样条分析(BARS) 本例用于 数据平滑处理-Bayesian Adaptive Regression Splines (BARS) Data smooth
bayesian-regression
- 贝叶斯回归算法以及几个仿真文件和仿真数据-bayesian algorithm and several test programs as well as the test data
RVM2
- 基于稀疏贝叶斯框架的机器学习算法,能有效用于回归和分类预测,具有较强的泛化性-Machine learning algorithm based on sparse Bayesian framework, can effectively be used for regression and classification forecast has good generalization
R001.m
- 贝叶斯回归分析,以二维图像线性拟合为例,解决过度拟合问题-Bayes regression
LSSVM
- 最小二乘支持向量机工具箱1.6版。含稳健回归和贝叶斯推理,功能强大。-LS-SVM Toolbox version 1.6. With robust regression and Bayesian inference, and powerful.
LSSVMLab-1.6
- lssvm工具箱,用途广泛,可用于分类,回归,贝叶斯等-lssvm nbc
ml-py
- 机器学习算法(kNN、逻辑回归、线性回归、朴素贝叶斯)python实现。-machine learning by python
classification-Python
- python实现感知器、贝叶斯分类、决策树分类、K最近邻法、逻辑回归、支持向量机-Python implementation of perceptron, Bias classification, decision tree classification, K nearest neighbor method, logic regression, support vector machine
naive_bayes
- 朴素贝叶斯算法分类及回归,附带训练集和测试集,可以评测正确率和输出预测文件(Classification and regression of naive Bayes algorithm, incidental training set and test set can evaluate the correct rate and output prediction file.)
bayesian_regression
- 贝叶斯回归是一个很好的回归模型。相对与其他模型,贝叶斯回归可以避免因为模型过简单或者过复杂而产生的拟合不足和过拟合的问题。(Bayesian Regression is a good regression model. Compared with other models, Bayesian Regression can avoid the problems of Under-fitting and Over-fitting resulting from the simple or too co
锂电池退化GPR
- 高斯过程回归是一种基于贝叶斯原理的统计机器学习方法,将先验分布通过贝叶斯定理转化成后验分布,与其他没有采用贝叶斯技巧的预测方法而言,高斯过程最大的优点是能方便地推断出超参数,同时也能方便地给出预测值的置信区间(Gaussian Process Regression is a statistical machine learning method based on Bayesian principle. It transforms prior distribution into posterio
贝叶斯向量自回归MATLAB代码
- 使用matlab实现贝叶斯向量自回归模型,可用于经济学中的预测(It can realize Bayesian vector autoregressive model, and it can be used to predict in economics.)