Datenvektor

A Datenvektor, also known as a data vector, is a fundamental concept in computer science and mathematics, particularly in the fields of data analysis, machine learning, and statistics. It is a one-dimensional array or list of data elements, typically of the same data type, such as integers, floats, or strings. Datenvektoren are used to represent and manipulate collections of data in a structured and efficient manner.

In the context of machine learning, Datenvektoren are often used to represent feature vectors, which are sets of numerical features that describe an instance or observation. For example, in a dataset of housing prices, a Datenvektor might represent the features of a single house, such as its size, number of bedrooms, and location. These feature vectors are then used as inputs to machine learning algorithms to train models and make predictions.

Datenvektoren are also commonly used in linear algebra, where they are represented as column or row vectors. These vectors can be manipulated using various operations, such as addition, subtraction, and scalar multiplication, to perform tasks like solving systems of linear equations or performing transformations on data.

In summary, a Datenvektor is a versatile and essential data structure used to represent and manipulate collections of data in various domains. Its simplicity and efficiency make it a valuable tool for data analysis, machine learning, and other related fields.