Clustering and Classification
Clustering and Classification methods are used to determine the similarity or dissimilarity among samples. Clustering methods are usually exploratory analysis methods which elucidate the similarity within a set of samples. They are often used to determine if there are natural groupings and/or particularly unique individuals or groups within a set. Classification, on the other hand, uses data with known group assignments and attempts to determine which group(s), if any, a new sample belongs to. This course will discuss various clustering and classification methods and the practical considerations for using them. The course includes hands-on computer time for participants to work example problems using PLS_Toolbox.
- Linear Discriminant Analysis
- K-Nearest Neighbors (KNN)
- PLS Discriminant Analysis
- Complex Classification Problems