Implementing Machine Learning Algorithm : Linear Discriminant Analysis (LDA) on the data-set of Different Flavors of Vines
Linear Discriminant Analysis (LDA) is a dimensionality reduction technique. As the name implies dimensionality reduction techniques reduce the number of dimensions (i.e. variables) in a dataset while retaining as much information as possible. For instance, suppose that we plotted the relationship between two variables where each color represent a different class
Compute the within class and between class scatter matrices
Compute the eigenvectors and corresponding eigenvalues for the scatter matrices
Sort the eigenvalues and select the top k
Create a new matrix containing eigenvectors that map to the k eigenvalues
Obtain the new features (i.e. LDA components) by taking the dot product of the data and the matrix from step 4