Short answer: feature selection is one particular method of dimensionality reduction. And most people when they say feature selection mean deliberate domain-dr

Short answer: feature selection is one particular method of dimensionality reduction. And most people when they say feature selection mean deliberate domain-driven selection of features. That is to say, you can also create an entirely new synthesized feature from, say, 5 raw features and use it to replace those 5 features (this is ... PCA-esque.) Or you could also use random forest techniques for example which just arbitrarily reduce the dimensions / features of each individual decision tree in the forest. I agree many people here are making mountains out of molehills of terminology.