• CSS3 linear gradient


    CSS3 linear gradient Definition and usage The linear gradient() function creates an “image” of a linear gradient. To create a linear gradient, you need to set a starting point and a direction (specified as an angle). You also define the termination color. The stop color is the transition you want gecko to smooth, and you […]

  • Professional English for machine learning


    Algorithm, algorithmClassification problemDataset datasetGenetic dataGradient descent methodK – means clusteringKernels kernelLinear modelLinear regressionMapping mappingRegression problemSupervised learningUnsupervised learningThe normal equations Professional English This work adoptsCC agreement, reprint must indicate the author and the link to this article Hacking

  • R language linear mixed effect model combat case


    Original link:http://tecdat.cn/?p=3015 introduce First, notice that the terminology around the multi-level model is very inconsistent. For example, a multi-level model itself may be called a hierarchical linear model, a random effect model, a multi-level model, a random intercept model, a random slope model, or a set model. According to different disciplines, software used and academic […]

  • Regression analysis of R language interval data


    Original linkhttp://tecdat.cn/?p=14850 Regression analysis is a very common data analysis method, which determines the relationship between variables through observation data. Traditional regression analysis takes point data as the research object, and the prediction result is also point data, while the real data often changes within a certain range. Based on the confidence degree, the confidence […]

  • “Canvas animation every Monday” – wave motion


    In the previous section, we introduced the contents of trigonometric functions in canvas animation and an arrow animation that rotates with the mouse. This section mainly introduces the waveform motion of trigonometric function. include: Smooth motion Linear motion Pulse motion 1. Waveform of sin function The waveform of sin function must be familiar to the […]

  • Python implements Bayesian linear regression model with pymc3


    Original link:http://tecdat.cn/?p=5263 In this paper, we will introduce regression modeling into Bayesian framework and use pymc3 MCMC library for reasoning. We will first review the multiple linear regression method of classical frequency theory. Then discuss how Bayesian considers linear regression. Bayesian linear regression with pymc3 In this section, we will make a statistical exampleclassicThe method […]

  • [machine learning notes]: boasting linear regression (I)


    Hello, I’m Dongge. As one of the classical regression models in supervised learning, linear regression is a very good start for beginners. Considering the concept of comprehensiveness from a macro perspective, I think we may have been in contact in junior middle school. Y = ax, X is the independent variable, y is the dependent […]

  • Block Gibbs Gibbs sampling Bayesian multiple linear regression in R language


    Original link:http://tecdat.cn/?p=11617 Original source:Tuo end data tribal official account In this article, I will use Gibbs sampling of block for multiple linear regression to obtain the conditional posterior distribution required for Gibbs sampling of block. Then, the sampler is coded and tested with simulated data. Bayesian model Suppose we have a sample size of the […]

  • 15000 star! Mathematical principles of popular machine learning algorithms


    [introduction]: the GitHub project recommended in this paper uses Python to implement popular machine learning algorithms, including the analysis behind the algorithm implementation. Each algorithm has an interactive jupyter notebook demo, which you can use to train data and algorithm configuration, and view results, charts and forecasts in a browser in real time. brief introduction […]

  • Machine learning (2): understand linear regression and gradient descent and make simple prediction


    Prediction begins with guesswork PressLast articleMachine learning is the process of applying mathematical methods to find laws in data. Since mathematics is the interpretation of the real world, let’s return to the real world and make some comparative imagination. Imagine that there is a white board made of plastic foam in front of us. There […]

  • Multiple regression analysis of Statistical Science


    01. Preface In front of us, we talked about univariate linear regression. If you haven’t seen it, you can take a look at it first: [univariate linear regression analysis]. In this article, let’s talk about multiple linear regression. Univariate linear regression means that there is only one X in the independent variable, while multivariate linear […]

  • Tecdat: R language portfolio optimization Solver: constrained optimization and nonlinear programming


    Link to the original text:http://tecdat.cn/?p=22853 This paper introduces different solvers in r that can be used for portfolio optimization. Universal solver The general solver can deal with any nonlinear optimization problem, but the cost may be slow convergence. defaultpackage The package stats (basic R package installed by default) provides several general optimizations. optimize()。 For one-dimensional […]