Feature Extraction, Construction and Selection

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning (2021, methodology): “For decreasing the dimensionality of the dataset, there are various feature engineering and feature selection techniques which can be used to remove that data not having that much importance in the dataset [18].”
The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data (2015, background): “The term feature transformation is not commonly used in the brain decoding community, but it is known in the machine learning community as a set of methods that change the meaning of each individual feature (Liu and Motoda, 1998).”
An Introduction to Feature Extraction (2006, background): “In this section, we present a unified view of feature selection that transcends the old cleavage filter/wrapper and is inspired by the views of (Liu and Motoda, 1998).”
Implementation of machine-learning classification in remote sensing: an applied review (2018, methodology): “In contrast, feature selection methods select a subset of the original variables that are determined to be valuable for the classi ﬁ cation (Khalid, Khalil, and Nasreen 2014; Liu and Motoda 1998; Mather 2004; Pal and Foody 2010).”