Feature (Data Science) 편집하기 (부분)

==Types of Features==
Features can take various forms depending on the type of data and the problem being solved:
*'''Numerical Features''': Continuous or discrete values, such as age, income, or temperature.
*'''Categorical Features''': Variables that represent distinct categories, such as gender, color, or product type.
*'''Ordinal Features''': Categorical features with an inherent order, such as education level or customer satisfaction rating.
*'''Textual Features''': Features derived from text, often transformed into numerical form through techniques like TF-IDF or word embeddings.
*'''Temporal Features''': Time-based features that capture trends or seasonality, such as timestamps or day of the week.