Onehotkoodausta
Onehotkoodaus, also known as one-hot encoding, is a process used in machine learning and data preprocessing to represent categorical variables as numerical vectors. In this method, each category within a variable is assigned a unique binary vector. The length of this vector is equal to the total number of unique categories. For a given data point, the vector will have a '1' at the position corresponding to its category and '0's elsewhere. For example, if a variable "color" has categories "red", "blue", and "green", "red" might be represented as [1, 0, 0], "blue" as [0, 1, 0], and "green" as [0, 0, 1].
This technique is crucial because many machine learning algorithms, particularly those based on mathematical operations like