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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def add_model_from_params(self, name, fit_filters, predict_filters, model_expression, ytransform=None):
 """ Add a model by passing arguments through to `RegressionModel`. Parameters name : any Must match a groupby segment name. fit_filters : list of str Filters applied before fitting the model. predict_filters : list of str Filters applied before calculating new data points. model_expression : str A patsy model expression that can be used with statsmodels. Should contain both the left- and right-hand sides. ytransform : callable, optional A function to call on the array of predicted output. For example, if the model relation is predicting the log of price, you might pass ``ytransform=np.exp`` so that the results reflect actual price. By default no transformation is applied. """

        logger.debug(
            'adding model {} to group {}'.format(name, self.name))
        model = RegressionModel(
            fit_filters, predict_filters, model_expression, ytransform, name)
        self.models[name] = model