Tutoriais de Linguagem R e de RStudio

1. Veja a nossa página de Linguagem R::Instalação e Tutoriais

Tutoriais Básicos de RP com R

Exemplos Básicos de Código

Código para ler uma planilha em CSV para dentro de R:

read.csv(“nome-do-arquivo”, header = TRUE, sep = ",")

kNN e outras Métricas de Distância

1. k-nearest neighbors::Machine Learning in R for beginners de Karlijn Willems
2. KNN example in R de Ranjit Mishra
3. Your First Machine Learning Project in R Step-By-Step (supostamente um tutorial para ML usando estatística de machinelearningmastery.com, mas na verdade ensina o básico com bons exemplos – use já!)
   

Voronoi, Delaunay e Tesselação

Diagrama de voronoi criado com os pacotes deldir e ggplot2 em R do tutorial de Phillip Johnson

1. Voronoi Diagram and Delaunay Triangulation in R By Nathan Yau (usa deldir)
   1. Fontes
2. Creating Voronoi Diagrams with ggplot2 de Phillip Johnson (usa deldir)
3. Manual do pacote deldir para Delaunay Triangulation and Dirichlet (Voronoi) Tessellation
4. CRAN package deldir: Delaunay Triangulation and Dirichlet (Voronoi) Tessellation
5. Voronoi polygons with R de Carson Farmer (usa deldir, sp e rgdal)
6. Voronoi Treemaps in R de Paul Murrell da University of Auckland, Department of Statistics (apresenta um enfoque um pouco diferente)
7. Distância de Mahalanobis: Veja nossa página de Estatística

Pacotes de R

Pacotes mais usados de R de acordo com o CRAN daily downloads:

1. e1071 Functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier etc 
2. rpart Recursive Partitioning and Regression Trees.
3. igraph A collection of network analysis tools.
4. nnet Feed-forward Neural Networks and Multinomial Log-Linear Models.
5. randomForest Breiman and Cutler’s random forests for classification and regression.
6. caret package (short for Classification And REgression Training) is a set of functions that attempt to streamline the process for creating predictive models.
7. kernlab Kernel-based Machine Learning Lab.
8. glmnet Lasso and elastic-net regularized generalized linear models.
9. ROCR Visualizing the performance of scoring classifiers.
10. gbm Generalized Boosted Regression Models.
11. party A Laboratory for Recursive Partitioning.
12. arules Mining Association Rules and Frequent Itemsets.
13. tree Classification and regression trees.
14. klaR Classification and visualization.
15. RWeka R/Weka interface.
16. ipred Improved Predictors.
17. lars Least Angle Regression, Lasso and Forward Stagewise.
18. earth Multivariate Adaptive Regression Spline Models.
19. CORElearn Classification, regression, feature evaluation and ordinal evaluation.
20. mboost Model-Based Boosting.