diff --git a/README.md b/README.md index 9c2c0bd4..0a2049f9 100644 --- a/README.md +++ b/README.md @@ -687,7 +687,6 @@ regression * [rgp](http://cran.r-project.org/web/packages/rgp/index.html) - rgp: R genetic programming framework * [arules](http://cran.r-project.org/web/packages/arules/index.html) - arules: Mining Association Rules and Frequent Itemsets * [frbs](http://cran.r-project.org/web/packages/frbs/index.html) - frbs: Fuzzy Rule-based Systems for Classification and Regression Tasks -* [e1071](http://cran.r-project.org/web/packages/e1071/index.html) - e1071: Misc Functions of the Department of Statistics (e1071), TU Wien * [rattle](http://cran.r-project.org/web/packages/rattle/index.html) - rattle: Graphical user interface for data mining in R * [ahaz](http://cran.r-project.org/web/packages/ahaz/index.html) - ahaz: Regularization for semiparametric additive hazards regression * [arules](http://cran.r-project.org/web/packages/arules/index.html) - arules: Mining Association Rules and Frequent Itemsets @@ -705,7 +704,6 @@ evaluation * [CoxBoost](http://cran.r-project.org/web/packages/CoxBoost/index.html) - CoxBoost: Cox models by likelihood based boosting for a single survival endpoint or competing risks * [Cubist](http://cran.r-project.org/web/packages/Cubist/index.html) - Cubist: Rule- and Instance-Based Regression Modeling -* [e1071](http://cran.r-project.org/web/packages/e1071/index.html) - e1071: Misc Functions of the Department of Statistics (e1071), TU Wien * [earth](http://cran.r-project.org/web/packages/earth/index.html) - earth: Multivariate Adaptive Regression Spline Models * [elasticnet](http://cran.r-project.org/web/packages/elasticnet/index.html) - elasticnet: Elastic-Net for Sparse Estimation and Sparse PCA * [ElemStatLearn](http://cran.r-project.org/web/packages/ElemStatLearn/index.html) - ElemStatLearn: Data sets, functions and examples from the book: "The Elements @@ -781,6 +779,7 @@ Angle Regression * [caret](http://caret.r-forge.r-project.org/) - Unified interface to ~150 ML algorithms in R. * [SuperLearner](https://github.com/ecpolley/SuperLearner) and [subsemble](http://cran.r-project.org/web/packages/subsemble/index.html) - Multi-algorithm ensemble learning packages. * [Introduction to Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/) +* [fpc](http://cran.r-project.org/web/packages/fpc/index.html) - fpc: Flexible procedures for clustering #### Data Analysis / Data Visualization