Use in Artificial Intelligence, Machine Learning, and Statistics
In artificial intelligence or machine learning, a training set consists of an input vector and an answer vector, and is used together with a supervised learning method to train a knowledge database (e.g. a neural net or a naive bayes classifier) used by an AI machine.
In statistical modeling, a training set is used to fit a model that can be used to predict a "response value" from one or more "predictors." The fitting can include both variable selection and parameter estimation. Statistical models used for prediction are often called regression models, of which linear regression and logistic regression are two examples.
In these fields, a major emphasis is placed on avoiding overfitting, so as to achieve the best possible performance on an independent test set that follows the same probability distribution as the training set.
Read more about this topic: Training Set
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