#NEWLINE# def next( self ) : #NEWLINE# #INDENT# "\n        Fit one boosting stage, returning a new\n        :class:`~pyfora.algorithms.regressionTrees.GradientBoostedRegressorBuilder.IterativeFitter`\n        object that holds the next regression model and predictions.\n\n        Examples::\n\n            from pyfora.algorithms import GradientBoostedRegressorBuilder\n\n            builder = GradientBoostedRegressorBuilder(1, 1, 1.0)\n            x = pandas.DataFrame({'x0': [-1,0,1], 'x1': [0,1,1]})\n            y = pandas.DataFrame({'y': [0,1,1]})\n\n            fitter = builder.iterativeFitter(x, y)\n\n            # compute scores vs number of boosts\n            numBoosts = 5\n            scores = []\n            for ix in xrange(numBoosts):\n                fitter = fitter.next()\n                scores = scores + [fitter.model.score(x, y)]\n\n        " #NEWLINE# ( pseudoResiduals , newPredictions ) = self . model . pseudoResidualsAndPredictions ( self . predictions ) #NEWLINE# newModel = self . model . boost ( newPredictions , pseudoResiduals ) #NEWLINE# return IterativeFitter ( newModel , newPredictions )