Principle-Component-Analysis
PCA is a technique to convert high dimensional data to low dimensions by removing insignificant variables in a dataset and thus decreasing redundancy. Application of this statistical method can be seen here on a sample gait data as well as on my Gait Analysis Research Project which will be uploaded soon.
