线性拟合的matlab仿真代码，包含数据点的收集、一般最小二乘算法、正交回归算法，画图等。其中数据点的收集还包括曲线的数据点收集。

SPSS 25 回归方法（Regression）IBM官方说明手册，繁体中文版。

Regression Modeling Strategies.pdf

用cnn回归进行的图像配准，比传统图像配准算法更快更准确的得到配准参数

基于java实现的一元线性回归代码，包括三个类

Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics. These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multiple regression, principal components, canonical variates, linear discriminant analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit, neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, boosting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another unique feature of this book is the discussion of database management systems. This book is appropriate for advanced undergraduate students, graduate students, and researchers in statistics, computer science, artificial intelligence, psychology, cognitive sciences, business, medicine, bioinformatics, and engineering. Familiarity with multivariable calculus, linear algebra, and probability and statistics is required. The book presents a carefully-integrated mixture of theory and applications, and of classical and modern multivariate statistical techniques, including Bayesian methods. There are over 60 interesting data sets used as examples in the book, over 200 exercises, and many color illustrations and photographs.

利用matlab代码实现的图像修复， 采用线性回归的方法，有样例，可直接运行

使用逻辑回归对iris数据集进行分类，只选取了前2种花的部分样本。java实现。

Image Deformation Using Moving Least Squares 算法的matlab实现。通过移动的最小二乘法改变和自定义的控制点操作图片。

内含完整的逻辑回归数据集，已经逻辑回归训练，训练完成后的模型测试部分（包括代码和完成数据集），用python3编码，可直接运行。训练完成后可直接显示点的颜色和分布，以及训练得到的直线。