models_classification.py 文件源码

def export_model(self, IDcol):
        #Export the model into the model file as well as create a submission 
        #with model index. This will be used for creating an ensemble.
        self.export_model_base(IDcol,'decision_tree')

    ## UNDER DEVELOPMENT CODE FOR PRINTING TREES
    # def get_tree(self):
    #     return self.alg.tree_
    # Print the tree in visual format
    # Inputs:
    #     export_pdf - if True, a pdf will be exported with the 
    #     filename as specified in pdf_name argument
    #     pdf_name - name of the pdf file if export_pdf is True
    # def printTree(self, export_pdf=True, file_name="Decision_Tree.pdf"):
    #     dot_data = StringIO() 
    #     export_graphviz(
    #             self.alg, out_file=dot_data, feature_names=self.predictors,
    #             filled=True, rounded=True, special_characters=True)

    #     export_graphviz(
    #         self.alg, out_file='data.dot', feature_names=self.predictors,  
    #         filled=True, rounded=True, special_characters=True
    #         ) 
    #     graph = pydot.graph_from_dot_data(dot_data.getvalue())

    #     if export_pdf:
    #         graph.write_pdf(file_name)

    #     return graph

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##### RANDOM FOREST
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