The strategy parameter determines which strategy the DummyClassifier will use to predict a class label.
- strategy = "stratified". The DummyClassifier makes random predictions based on the distribution of the training data.
- strategy = "uniform". DummyClassifier will generate predictions uniformly at random.
- strategy = "most_frequent". DummyClassifier will always predict the most frequent class label in the training dataset.
- strategy = "constant". This is most often used when classifying non-majority class labels. The DummyClassifier will always predict a constant label, which is provided by the user.

University of Michigan - Ann Arbor

Scikit-learn allows for dummy classifiers to be created for the purpose of comparing to a statistically generated model

```
dummy = DummyClassifier(strategy="most_frequent")
```

This code creates a dummy classifier which predicts every value to hold the same value as the most frequent value in the training set. 

sklearn.dummy.DummyClassifier

https://scikit-learn.org/stable/user_guide.html

Scikit-learn Documentation

DummyClassifier strategy parameter

The DummyRegressor is similar to the DummyClassifier. While a DummyClassifier can serve as a baseline for comparison with real classifiers, a DummyRegressors can serve as a baseline for comparison with real regressors. 

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