Dimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally close to its intrinsic dimension. Working in high-dimensional spaces can...

Why do we need to impute missing data values?# Before going ahead with imputation, let us understand what is a missing value. So, a missing value is the part of the dataset that seems missing or is a null value, maybe due to some missing data during research or data collection. Having a missing value in a machine...