python machine-learning linear-regression-models xgboost-algorithm Updated Feb 15, 2025 Jupyter Notebook s1dewalker / Model_Validation Star 0 Code Issues Pull requests Model Management in Python. Steps involved in Model Validation and tuning. Testing Model Assumptions in Factor Analysis with OLS...
Code README linear_regression_project This project implements linear regression using both gradient descent and normal equations. The project includes several components to demonstrate the concepts of linear regression and its implementation in Python. ...
PyTorch 基础篇(2):线性回归(Linear Regression) 发布于 2023-12-07 13:04:55 30502 代码可运行 文章被收录于专栏:二猫の家 代码语言:javascript 代码运行次数:0 运行 AI代码解释 #包importtorchimport torch.nnasnnimport numpyasnpimport matplotlib.pyplotasplt...
J_history=np.zeros((num_iters,1))foriterinrange(num_iters):# 对J求导,得到 alpha/m*(WX-Y)*x(i),(3,m)*(m,1)X(m,3)*(3,1)=(m,1)theta=theta-(alpha/m)*(X.T.dot(X.dot(theta)-y))J_history[iter]=computeCost(X,y,theta)returnJ_history,theta iterations=10000#迭代次数 alph...
Simple Linear Regression Data set and code for ipython notebook pleace click the github link below. Data from 2016 shanghai Annals of Statistics. In statistics, simple linear regression is a linear regression model with a single explanatory variable. That is, it concerns two-dimensional sample po...
通过看其他人在kaggle上分享的notebook以及自己的一些理解,记录一下Linear Regression的学习过程,也算是完成作业中的report.pdf。 二、Linear Regression(预测PM2.5) 1、准备工作 (1)作业要求(如图一所示) 图一 (2)train.csv、test.csv 链接:https://pan.baidu.com/s/1ZeOASD7SdyMUYwjo0uDaqA ...
吴恩达机器学习(十三)—— ex5:Regularized Linear Regression and Bias v.s. Variance(MATLAB+Python),一、线性回归的正则化1.1可视化数据集1.2正则化线性回归的代价函数1.3线性回归梯度的正则化1.4拟合线性回归二、偏差和方差2.1学习曲线三、多项式回归3.1学习多项
Scikit-learn [57] is a well known Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised ML problems. It supports tools for classification, regression, clustering, dimensionality reduction, model selection and preprocessing. ...
Written By Troy Walters Program Python Published Jul 10, 2017 In my last post I demonstrated how to obtain linear regression parameter estimates in R using only matrices and linear algebra. Using the well-known Boston data set of housing characteristics, I calculated ordinary least-squares ...
We still haven’t really seen the benefit of this vector notation (and we won’t see it’s true power until we extend this to kernel ridge regression in the next post), but we do have at least one additional notational convenience: we can add arbitrarily many input variables without chang...