Principal Component, Unsupervised Learning, Dimensionality Reduction, Interview Questions, Machine Learning.
two) (A) Some information is lost, possibly degrading the performance of subsequent training algorithms. (B) Transformed features are often hard to interpret. (C) Helps visualize the data on 2D plots or 3D plots. (D) Less data means less storage space required. Fewer dimensions mean less computing.