Linear Discriminant Analysis in R | Example with Classification Model & Bi-Plot interpretation

Provides steps for carrying out linear discriminant analysis in r and it's use for developing a classification model. R file: https://github.com/bkrai/R-files-from-YouTube Timestamps: 00:00 Linear Discriminant Analysis 00:51 Iris Data 02:56 Data Partition 04:15 Linear Discriminant Analysis 07:03 Stacked Histograms of Discriminant Function Values 10:59 Bi-Plot interpretation 14:45 Partition Plots 16:34 Confusion Matrix & Accuracy - Training Data 18:48 Confusion Matrix & Accuracy - Testing Data 19:45 Linear Discriminant Analysis Advantage 19:59 Linear Discriminant Analysis Limitation linear discriminant analysis is an important statistical tool related to analyzing big data or working in data science field. R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.