<gh_stars>0
class RegressionMetric:
    '''Base class for all regression metrics. Meant to be inherited and overridden.'''

    def __init__(self, name, latex_name, id):
        '''Initialize metric with name, LaTeX name and ID.'''
        self.name = name
        self.latex_name = latex_name
        self.id = id

    def evaluate(self, X, y_test, y_pred):
        '''Evaluate the metric for multiple predictions, given their corresponding true values.'''
        pass

    def rank(self, values):
        '''Transform metric values to sortable keys wherein the lowest key value corresponds to the best-performing model.'''
        pass

class RegressionMetric:
    '''Base class for all regression metrics. Meant to be inherited and overridden.'''

    def __init__(self, name, latex_name, id):
        '''Initialize metric with name, LaTeX name and ID.'''
        self.name = name
        self.latex_name = latex_name
        self.id = id

    def evaluate(self, X, y_test, y_pred):
        '''Evaluate the metric for multiple predictions, given their corresponding true values.'''
        pass

    def rank(self, values):
        '''Transform metric values to sortable keys wherein the lowest key value corresponds to the best-performing model.'''
        pass
Base class for all regression metrics. Meant to be inherited and overridden. Initialize metric with name, LaTeX name and ID. Evaluate the metric for multiple predictions, given their corresponding true values. Transform metric values to sortable keys wherein the lowest key value corresponds to the best-performing model.