You should use R for machine learning. R is one of the most powerful machine learning platforms and is used by the top data scientists in the world. In this post you will learn why you should use R for machine learning. Let’s get started. Why You Should Care About R R is used by […]
The Caret R package allows you to easily construct many different model types and tune their parameters. After creating and tuning many model types, you may want know and select the best model so that you can use it to make predictions, perhaps in an operational environment. In this post you discover how to compare […]
Selecting the right features in your data can mean the difference between mediocre performance with long training times and great performance with short training times. The caret R package provides tools to automatically report on the relevance and importance of attributes in your data and even select the most important features for you. In this […]
Machine learning algorithms are parameterized so that they can be best adapted for a given problem. A difficulty is that configuring an algorithm for a given problem can be a project in and of itself. Like selecting ‘the best’ algorithm for a problem you cannot know before hand which algorithm parameters will be best for […]
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 […]
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 […]
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 […]
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 […]
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 […]
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. Let’s get […]
