Dimensionality Reduction in Machine Learning

Introduction Dimensionality Reduction in machine learning is the conversion of data from a high-dimensional space into a low-dimensional space. This is so that the low-dimensional representation recalls certain expressive properties of the original data that is preferably close to its basic dimension. At work in high-dimensional spaces may be unwanted for many reasons for example; … Read more