Data Science, Machine Learning, Technology, Data, Dimensionality Reduction.
information when in a lower dimension. The basic idea is this: we want to rotate the data such that we can find an orthogonal basis for it, then use only the orthogonal vectors that have the most variance. It’s easiest to conceptualize when working in three dimensions. Why not use our mallet