In scikit-learn, an estimator is an object that implements the methods required for learning from data and making predictions. Estimators are used to fit a model to a dataset, which involves learning the parameters of the model based on the input data.
There are two main types of estimators in scikit-learn:
-
Transformers: These estimators are used to preprocess data, such as scaling or normalizing features. They implement the
fitandtransformmethods. -
Predictors: These estimators are used for making predictions after fitting a model. They implement the
fitandpredictmethods.
For example, a linear regression model is an estimator that can be used to predict a continuous target variable based on input features. You can create an estimator, fit it to your data, and then use it to make predictions.
