A Glossary & terminology

This thesis was written in statistics terms. This glossary helps bridge the language used here to be more accessible to machine learning audiences.

Term	Alias	Terminology
data		\(X_{n \times p}\)
observation	instance, item, case, row (of data)	\(X_{i \times .} | i \in [1, n]\)
variable	feature, column (of data)	\(X_{. \times j} | j \in [1, p]\)
basis	linear combination of variables, their orientations	\(A_{p \times d} | A\) is orthonormal
linear projection	linear embedding	\(Y_{n \times d} = X_{n \times p} \times A_{p \times d}\)
explanatory variables	independent-/input- variables, predictors, covariates	not used
response variable	predicted-/dependent-/target-/output- variable	not used