Quadratic Discriminant Analysis of Several Groups

Quadratic discriminant analysis for classification is a modification of linear discriminant analysis that does not assume equal covariance matrices amongst the groups [latex](\Sigma_1, \Sigma_2, \cdots, \Sigma_k)[/latex]. Similar to LDA for several groups, quadratic discriminant analysis of several groups classification seeks to find the group that maximizes the quadratic classification function...

LDA for Classification into Several Groups

Similar to the two-group linear discriminant analysis for classification case, LDA for classification into several groups seeks to find the mean vector that the new observation [latex]y[/latex] is closest to and assign [latex]y[/latex] accordingly using a distance function. The several group case also assumes equal covariance matrices amongst the groups...

Quadratic Discriminant Analysis of Two Groups

As mentioned in the post on classification with linear discriminant analysis, LDA assumes the groups in question have equal covariance matrices [latex](\Sigma_1 = \Sigma_2 = \cdots = \Sigma_k)[/latex]. Therefore, often when the groups do not have equal covariance matrices, observations are frequently assigned to groups with large variances on the...

Classification with Linear Discriminant Analysis

Classification with linear discriminant analysis is a common approach to predicting class membership of observations. A previous post explored the descriptive aspect of linear discriminant analysis with data collected on two groups of beetles. In this post, we will use the discriminant functions found in the first post to classify...

Predicting Extramarital Affairs with Decision Trees and R

In this example, we'll build classification decision trees to analyze if a particular individual will commit an affair on their partner based on demographics and other data. Getting Started Start by loading the packages we will use in the analysis. The rpart package is the main workhorse for building and analyzing decision...

Using Logistic Regression to Model and Predict Category Values

Introduction In this post, we will learn more about using logistic regression to classify and predict categorical values. An introduction to classification and logistic regression will be discussed in order to provide a foundation to understanding and explaining the various methods available in classification problems and its outputs. Lastly, an example...