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chapter_07
- 通过几个特征对iris种类预测，机器学习，多元应用回归分析(iris prediction, using machine learning to analyse several characters to predict)
基于PCA_FOA_SVR的股票价格预测研究_王卫红
- SVM应用举例,利用svm回归分析，预测股市指数，支持向量机回归(Application examples of svm)
house_price
- Python语言，房价预测，简单线性回归，TXT类型数据。(Python,House price forecast)
logisticRegressionshiyan线性回归
- 用于数据挖掘，疾病自动诊断，经济预测等领域。例如，探讨引发疾病的危险因素，建立Logistics回归模型，并根据此预测疾病发生的概率等(Used for data mining, disease automatic diagnosis, economic forecasting and other fields. For example, to explore the risk factors for disease, establish Logistics regression model,
liner_regression
- 在MATLAB实现了线性回归算法，并对给定的数据做出了预测(A linear regression algorithm is implemented in MATLAB, and the prediction of the given data is made.)
pso-svr代码
- 基于粒子群优化的向量回归预测分析 matlab代码(Support vector regression code with pso)
GPR based on GPML-V4.1
- 基于 gpml-matlab-v4.1 工具箱，简单实现了高斯过程回归（Gaussian process regression，GPR）的多变量数据回归，给出了每个预测值的均值以及对应的方差。代码有详细的注释，附有训练数据和测试数据。(Based on the gpml-matlab-v4.1 toolbox, Gaussian process regression (GPR) multivariate data regression is simply implemented, and the
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
Matlabbp神经网络
- bp神经网络，可以用于预测与回归，效果比较好，注意训练次数(BP Neural network algorithm)
7175674gaussian
- GPR程序，可以用于高斯过程回归预测，预测均值和方差(GPR program can be used for regression prediction of Gauss process, prediction of mean and variance.)
采用广义回归神经网络GRNN进行货运量预测
- 针对货运量预测问题，建立广义神经网络，对货运量进行预测。同时建立了BP神经网络，通过预测误差进行比较(Aiming at the problem of freight volume prediction, a generalized neural network is established to predict freight volume. At the same time, a BP neural network is established to compare the predicti
SVMcgForRegress
- 支持向量机中的支持向量回归函数对数据进行预测(Support Vector Regression Function in Support Vector Machine to Predict Data)
Logistic.m
- 预测未来几年的人口，采用逻辑回归模型预测，用的数据是87-20年的数据(Forecasting the population of the next few years)
3116001336(2)
- 建立一个 logistic 回归模型来预测学生是否被录取到大学。使用高级优化来获得最佳的theta和最小的cost。(To get started with the exercise, you will need to download the starter code and unzip its contents to the directory where you wish to complete the exercise. If needed, use the cd command i
ga_aco_opt_on_anfis_svm-master
- 利用遗传算法、蚁群算法、PSO等对SVM模型进行优化，实现高效分类和回归预测(The SVM model is optimized by genetic algorithm, ant colony algorithm and PSO to achieve efficient classification and regression prediction.)
免疫+ELM 回归
- 用免疫算法优化ELM的输入层到隐藏层的权值与阈值参数，以此来提高ELM的预测精度。(Optimizing ELM parameters with immune algorithms)
PCAR
- 主成分回归算法的python实现，用于进行预测的问题(Python implementation of principal component regression algorithm for prediction)
机器学习实战书+源代码
- 机器学习横跨计算机科学、工程科学和统计学等多个学科，需要多学科的专业知识。在需要解释并操作数据的领域都或多或少可以运用到机器学习，通过这本书可以系统地学习基于python语言的机器学习的相关知识(Machine Learning in Action written by Peter Harringto. Machine learning covers many subjects, such as computer science, engineering science and statisti
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.)
nes_logistic
- 基于贝叶斯理论的logistic回归模型的建立、预测。(The establishment and prediction of logistic regression model based on Bayesian theory.)