Mean Learner ============ .. figure:: icons/mean-learner.png Learns the mean of its input data. Signals ------- **Inputs**: - **Data** A data set. - **Preprocessor** Preprocessed data. **Outputs**: - **Learner** A mean learning algorithm. - **Predictor** A trained regressor. Signal *Predictor* sends the regressor only if signal *Data* is present. Description ----------- This is the simplest learner widget for regression problems. It *learns* the mean of the class variable and returns a predictor with the same `mean value `_. Due to its accuracy, this widget can serve as a baseline for other regression models. .. figure:: images/Mean-stamped.png 1. Learner/predictor name 2. Produce a report. 3. The *Apply* button commits changes to the output. Alternatively, tick the box on the left side of the button to apply changes automatically. Examples -------- In the first example, we use **Mean Learner** to construct a predictor and input it into the :doc:`Data Table<../data/datatable>`. We used the *housing* data set. In the table, you can see an extra column *Mean Learner* with one (mean) value for all instances. .. figure:: images/mean-learner-example1.png Another way to use **Mean Learner** is to compare it to other learners in the :doc:`Test&Score<../evaluation/testlearners>` widget. .. figure:: images/mean-learner-example2.png