eloszlásvektort

Eloszlásvektor is a Hungarian term that translates to "distribution vector" in English. It is a concept used in various fields, including statistics, machine learning, and computer science, to represent the probability distribution of a set of outcomes or variables.

In essence, an eloszlásvektor is a vector where each element corresponds to the probability of a specific event or the value of a particular variable. The sum of all elements in an eloszlásvektor must equal one, as it represents a complete probability distribution. For example, if we have a random variable that can take on three possible values, the eloszlásvektor would be a three-element vector, where each element represents the probability of observing each of those values.

Eloszlásvektorok are crucial for understanding and modeling uncertainty. They are used in algorithms for classification, regression, and anomaly detection. For instance, in machine learning, a classifier might output an eloszlásvektor representing the probability of an input belonging to each of several classes. Similarly, in statistical modeling, eloszlásvektorok can describe the likelihood of different parameter values. The term is particularly prevalent in Hungarian academic and technical literature concerning these subjects.