Модель

Traditionally, the parameters for the prediction function. For example, the weights in a linear regression model or the split points in a decision tree. In ML.NET, a model contains all the information necessary to predict the label of a domain object (for example, image or text). This means that ML.NET models include the featurization steps necessary as well as the parameters for the prediction function.

In general, any mathematical construct that processes input data and returns output. Phrased differently, a model is the set of parameters and structure needed for a system to make predictions. In supervised machine learning, a model takes an example as input and infers a prediction as output. Within supervised machine learning, models differ somewhat. For example: - A linear regression model consists of a set of weights and a bias. - A neural network model consists of: - A set of hidden layers, each containing one or more neurons. - The weights and bias associated with each neuron. - A decision tree model consists of: - The shape of the tree; that is, the pattern in which the conditions and leaves are connected. - The conditions and leaves. You can save, restore, or make copies of a model. Unsupervised machine learning also generates models, typically a function that can map an input example to the most appropriate cluster. An algebraic function such as the following is a model: The preceding function maps input values (x and y) to output. Similarly, a programming function like the following is also a model: A caller passes arguments to the preceding Python function, and the Python function generates output (via the return statement). Although a deep neural network has a very different mathematical structure than an algebraic or programming function, a deep neural network still takes input (an example) and returns output (a prediction). A human programmer codes a programming function manually. In contrast, a machine learning model gradually learns the optimal parameters during automated training.

Any model pre-trained or not. In general, any mathematical construct that processes input data and returns output. Phrased differently, a model is the set of parameters and structure needed for a system to make inferences.