## Cardinality The cardinality of a Set refers to the number of elements it contains.

In math notation, we represent the cardinality of a set $S$ as $|S|$. For example, the set $S = \{1, 2, 3\}$ has a cardinality of 3, expressed as $|S| = 3$.

In machine learning, the "cardinality of a feature" denotes the number of unique elements or categories within that feature. High-cardinality features may require feature engineering or be excluded entirely (for example, user_id).

## Use of the vertical bar |A| notation

Initially it seemed confusing to me that mathematical notation employs the vertical bar symbol for different purposes.

For instance:

• The absolute value of a number $a$ is expressed as $|a|$.
• The Matrix Determinate of a matrix $\mathbf{M}$ is expressed as $|\mathbf{M}|$:

\begin{aligned} \mathbf{M} = \begin{bmatrix} A & B \\ C & D \end{bmatrix} ,\quad |\mathbf{M}| = AD - BC \end{aligned}

However, these notations share a common theme of representing size or magnitude:

• In set theory, cardinality describes the size of a set by the number of elements it contains.
• For numbers, the absolute value captures the distance from zero on the number line.
• In linear algebra, the Matrix Determinate determinant describes how much a Matrix Transformation scales space.