We define a grid of hyperparameters to be explored by the [RandomizedSearchCV](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html). Using a [GridSearchCV](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html) instead would explore all the possible combinations on the grid, which can be costly to compute, whereas the parameter n_iter of the RandomizedSearchCV controls the number of different random combination that are evaluated. Notice that setting n_iter larger than the number of possible combinations in a grid would lead to repeating already-explored combinations. We search for the best parameter combination for both the feature extraction (vect__) and the classifier (clf__).