"A technique that attempts to combine or transform predictors to make clear the information contained within them. Feature extraction methods include factor analysis, principal components analysis, correspondence analysis, multidimensional scaling, partial least square methods, and singular value decomposition." (Robert Nisbet et al, "Handbook of statistical analysis and data mining applications", 2009)
"Extracting or deriving some useful information from the initially obtained data." (Shouvik Chakraborty & Kalyani Mali, "An Overview of Biomedical Image Analysis From the Deep Learning Perspective", 2020)
"A process of finding features of words and map them to vector space." (Neha Garg & Kamlesh Sharma, "Machine Learning in Text Analysis", 2020)
"A digital signal processing algorithm, which extracts distinctive values from the input signal." (Andrej Zgank et al, "Embodied Conversation: A Personalized Conversational HCI Interface for Ambient Intelligence", 2021)
"Feature extraction is a procedure in dimensionality reduction of extracting principal variables (features) from some random variables under consideration, usually achieved by extracting one principal variable (feature) as mapping from multiple random variables." (Usama A Khan & Josephine M Namayanja, "Reevaluating Factor Models: Feature Extraction of the Factor Zoo", 2021)
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