A collection of R code snippets with explanations. A set of basic examples can serve as an introduction to the language. R Examples. Welcome. Basics Functions Countdown User input Random number game Lists Reading data Filtering data. More Examples How to run the code Finding data sources. Welcome. The articles on the left provide an introduction to R for people who are already familiar with.

Confusion matrix is an important tool in measuring the accuracy of a classification, both binary as well as multi-class classification. Many a times, confusing matrix is really confusing! In this post, I try to use a simple example to illustrate construction and interpretation of confusion matrix.

R Matrix. In R, a two-dimensional rectangular data set is known as a matrix. A matrix is created with the help of the vector input to the matrix function. On R matrices, we can perform addition, subtraction, multiplication, and division operation. In the R matrix, elements are arranged in a fixed number of rows and columns. The matrix elements.

Create your own correlation matrix. Key decisions to be made when creating a correlation matrix include: choice of correlation statistic, coding of the variables, treatment of missing data, and presentation. An example of a correlation matrix. Typically, a correlation matrix is “square”, with the same variables shown in the rows and columns.

The igraph R package features an interactive graph layout editor for small graphs. It is a little toy only, but can be useful if you want to adjust the layout of small graphs. Here is how we generated this picture.

Confusion Matrix (caret) plotting: superior to base fourfoldplot()? Close. 3. Posted by 11 months ago. Archived. Confusion Matrix (caret) plotting: superior to base fourfoldplot()? I was surprised to discover in this Stack Overflow post that the best answer for plotting a confusion matrix output by the caret package was a function not contained in a package, as far as I know. That function.

The matrix structure offers organizations an effective system for managing projects. But it also involves much complexity and demands much communication so that all organizational managers--particularly the project and the functional--can effectively and efficiently work together. This article examines the matrix organization (MO). In doing so, it defines the MO and describes its operating.

Today: Confusion Matrix and Class Statistics. This first blog post lauds the confusion matrix - a compact representation of the model performance, and the source of many scoring metrics for classification models. A classification model assigns data to two or more classes. Sometimes, detecting one or the other class is equally important and bears no additional cost. For example, we might want.