Last Updated on August 22, 2019 R is perhaps one of the most powerful and most popular platforms for statistical programming and applied machine learning. When you get serious about machine learning, you will find your way into R. In this post, you will discover what R is, where it came from and some of its most important features. Kick-start your project with my new book Machine Learning Mastery With R, including step-by-step tutorials and the R source code files […]

Last Updated on August 22, 2019 In this post you will discover 7 recipes for non-linear classification with decision trees in R. All recipes in this post use the iris flowers dataset provided with R in the datasets package. The dataset describes the measurements if iris flowers and requires classification of each observation to one of three flower species. Kick-start your project with my new book Machine Learning Mastery With R, including step-by-step tutorials and the R source code files […]

Last Updated on August 22, 2019 Optimization is a big part of machine learning. It is the core of most popular methods, from least squares regression to artificial neural networks. In this post you will discover recipes for 5 optimization algorithms in R. These methods might be useful in the core of your own implementation of a machine learning algorithm. You may want to implement your own algorithm tuning scheme to optimize the parameters of a model for some cost […]

Last Updated on August 15, 2020 When you are building a predictive model, you need a way to evaluate the capability of the model on unseen data. This is typically done by estimating accuracy using data that was not used to train the model such as a test set, or using cross validation. The caret package in R provides a number of methods to estimate the accuracy of a machines learning algorithm. In this post you discover 5 approaches for […]

Last Updated on August 22, 2019 R is the most popular platform for applied machine learning. When you want to get serious with applied machine learning you will find your way into R. It is very powerful because so many machine learning algorithms are provided. A problem is that the algorithms are all provided by third parties, which makes their usage very inconsistent. This slows you down, a lot, because you have to learn how to model data and how […]

Last Updated on August 22, 2019 The R platform for statistical computing is perhaps the most popular and powerful platform for applied machine learning. The caret package in R has been called “R’s competitive advantage“. It makes the process of training, tuning and evaluating machine learning models in R consistent, easy and even fun. In this post you will discover the caret package in R, it’s key features and where to go to learn more about it. Kick-start your project […]

Last Updated on August 22, 2019 The caret package in R is designed to streamline the process of applied machine learning. A key part of solving data problems in understanding the data that you have available. You can do this very quickly by summarizing the attributes with data visualizations. There are a lot of packages and functions for summarizing data in R and it can feel overwhelming. For the purposes of applied machine learning, the caret package provides a few […]