def export(self, model_name, export_folder):
        """
        Export model and transformers to export_folder

        Parameters
        ----------
        model_name: string
            name of model to export
        export_folder: string
            folder to store exported model and transformers
        """
        for transformer in self.transformers:
            if isinstance(transformer, MultiLabelBinarizer):
                joblib.dump(transformer,
                            join(export_folder, "label.transformer.bin"),
                            protocol=2)
            if isinstance(transformer, TfidfVectorizer):
                joblib.dump(transformer,
                            join(export_folder, "tfidf.transformer.bin"),
                            protocol=2)
            if isinstance(transformer, CountVectorizer):
                joblib.dump(transformer,
                            join(export_folder, "count.transformer.bin"),
                            protocol=2)
            if isinstance(transformer, NumberRemover):
                joblib.dump(transformer,
                            join(export_folder, "number.transformer.bin"),
                            protocol=2)
        model = [model for model in self.models if model.name == model_name][0]
        e = Experiment(self.X, self.y, model.estimator, None)
        model_filename = join(export_folder, "model.bin")
        e.export(model_filename)
def export(self, model_name, export_folder):
        """
        Export model and transformers to export_folder

        Parameters
        ----------
        model_name: string
            name of model to export
        export_folder: string
            folder to store exported model and transformers
        """
        for transformer in self.transformers:
            if isinstance(transformer, MultiLabelBinarizer):
                joblib.dump(transformer,
                            join(export_folder, "label.transformer.bin"),
                            protocol=2)
            if isinstance(transformer, TfidfVectorizer):
                joblib.dump(transformer,
                            join(export_folder, "tfidf.transformer.bin"),
                            protocol=2)
            if isinstance(transformer, CountVectorizer):
                joblib.dump(transformer,
                            join(export_folder, "count.transformer.bin"),
                            protocol=2)
            if isinstance(transformer, NumberRemover):
                joblib.dump(transformer,
                            join(export_folder, "number.transformer.bin"),
                            protocol=2)
        model = [model for model in self.models if model.name == model_name][0]
        e = Experiment(self.X, self.y, model.estimator, None)
        model_filename = join(export_folder, "model.bin")
        e.export(model_filename)
def export ( self , model_name , export_folder ) : for transformer in self . transformers : if isinstance ( transformer , MultiLabelBinarizer ) : joblib . dump ( transformer , join ( export_folder , "label.transformer.bin" ) , protocol = 2 ) if isinstance ( transformer , TfidfVectorizer ) : joblib . dump ( transformer , join ( export_folder , "tfidf.transformer.bin" ) , protocol = 2 ) if isinstance ( transformer , CountVectorizer ) : joblib . dump ( transformer , join ( export_folder , "count.transformer.bin" ) , protocol = 2 ) if isinstance ( transformer , NumberRemover ) : joblib . dump ( transformer , join ( export_folder , "number.transformer.bin" ) , protocol = 2 ) model = [ model for model in self . models if model . name == model_name ] [ 0 ] e = Experiment ( self . X , self . y , model . estimator , None ) model_filename = join ( export_folder , "model.bin" ) e . export ( model_filename )
Export model and transformers to export_folder

        Parameters
        ----------
        model_name: string
            name of model to export
        export_folder: string
            folder to store exported model and transformers
Export model and transformers to export_folder