Eigenvectors, Principal Component, Dimensionality Reduction, Data Science, Unsupervised Learning.
increase of features. This is where the Dimensionality reduction techniques such as PCA or LDA come into play. They help in transforming the dataset of high dimensions into lower dimensions without having to lose the essence of the data. It looks like a magic wand transforming the data right?