#NEWLINE# def next( self ) : #NEWLINE# #INDENT# "\n        Boost once and return a new\n        :class:`~pyfora.algorithms.regressionTrees.GradientBoostedClassifierBuilder.IterativeFitter`\n\n        Returns:\n            A :class:`~pyfora.algorithms.regressionTrees.GradientBoostedClassifierBuilder.IterativeFitter`\n            instance.\n\n        Example::\n\n            from pyfora.algorithms import GradientBoostedClassifierBuilder\n\n            builder = GradientBoostedClassifierBuilder(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\n        " #NEWLINE# ( pseudoResiduals , regressionValues ) = self . model . pseudoResidualsAndRegressionValues ( self . previousRegressionValues ) #NEWLINE# newModel = self . model . boost ( pseudoResiduals ) #NEWLINE# return IterativeFitter ( pseudoResiduals , regressionValues )