목록Reference (45)
Linear Discriminant Analysis(LDA) and Quadratic Discriminant-Analysis(QDA)
https://www.statology.org/linear-discriminant-analysis-in-r/ Linear Discriminant Analysis in R (Step-by-Step) This tutorial explains how to perform linear discriminant analysis in R, including a step-by-step example. www.statology.org https://www.statology.org/quadratic-discriminant-analysis-in-r/ Quadratic Discriminant Analysis in R (Step-by-Step) This tutorial explains how to perform quadratic..
principal components regression
https://www.statology.org/principal-components-regression-in-r/ Principal Components Regression in R (Step-by-Step) This tutorial explains how to perform principal components regression in R, including a step-by-step example. www.statology.org
Causal Inference
https://medium.com/@leihua-ye/why-data-scientists-should-learn-causal-inference-a70c4ffb4809 Why Data Scientists Should Learn Causal Inference Climb up the ladder of causation leihua-ye.medium.com
Logistic regression
https://arunaddagatla.medium.com/maximum-likelihood-estimation-in-logistic-regression-f86ff1627b67 Maximum Likelihood Estimation in Logistic Regression The Maximum Likelihood Estimation (MLE) is a method of estimating the parameters of a logistic regression model. arunaddagatla.medium.com
Principal component analysis
https://stats.stackexchange.com/questions/2691/making-sense-of-principal-component-analysis-eigenvectors-eigenvalues/140579#140579 Making sense of principal component analysis, eigenvectors & eigenvalues In today's pattern recognition class my professor talked about PCA, eigenvectors and eigenvalues. I understood the mathematics of it. If I'm asked to find eigenvalues etc. I'll do it correctly l..