Fit a basic model using cross-validation

- [Instructor] Now that we have clean data … split into training, validation, and test sets, … in this lesson we're going to fit a single basic model … using cross validation. … The goal is just to get an understanding … of what the baseline level of performance might look like. … Now remember, this phase is going to take place … on only the training set. … So I'll go ahead and import all the packages we need … which will include RandomForceClassifier from scikit-learn, … that's the algorithm that we'll be using, … and cross_val_score … which will help us run our cross validation. … Also, we're going to import this warnings module … that we saw before … and we're going to tell it to filter future warnings. … Now as we saw before, … this will only suppress warnings in the future class. … The reason we're going to do that for this lesson … is because the default value for one of the hyper parameters … in RandomForceClassifier is going to change … in the future version of scikit-learn. …