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rgf_example.model()   A
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↳ Parent: rgf_example

Complexity

Conditions 1

Size

Total Lines 12
Code Lines 10

Duplication

Lines 0
Ratio 0 %

Importance

Changes 0
Metric Value
cc 1
eloc 10
nop 1
dl 0
loc 12
rs 9.9
c 0
b 0
f 0
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from sklearn.datasets import load_breast_cancer
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from sklearn.model_selection import cross_val_score
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from rgf.sklearn import RGFClassifier
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from hyperactive import Hyperactive

            


            
                                                                                                            
                            
            
                                    
            
            

                
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data = load_breast_cancer()

            


            
                                                                                                            
                            
            
                                    
            
            

                
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X, y = data.data, data.target

            


            
                                                                                                            
                            
            
                                    
            
            

                
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def model(opt):

            


            
                                                                        
                            
            
                                    
            
            

                
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    rgf = RGFClassifier(

            


            
                                                                        
                            
            
                                    
            
            

                
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        max_leaf=opt["max_leaf"],

            


            
                                                                        
                            
            
                                    
            
            

                
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        reg_depth=opt["reg_depth"],

            


            
                                                                        
                            
            
                                    
            
            

                
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        min_samples_leaf=opt["min_samples_leaf"],

            


            
                                                                        
                            
            
                                    
            
            

                
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        algorithm="RGF_Sib",

            


            
                                                                        
                            
            
                                    
            
            

                
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        test_interval=100,

            


            
                                                                        
                            
            
                                    
            
            

                
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        verbose=False,

            


            
                                                                        
                            
            
                                    
            
            

                
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    )

            


            
                                                                        
                            
            
                                    
            
            

                
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    scores = cross_val_score(rgf, X, y, cv=3)

            


            
                                                                        
                            
            
                                    
            
            

                
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    return scores.mean()

            


            
                                                                                                            
                            
            
                                    
            
            

                
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search_space = {

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    "max_leaf": list(range(10, 2000, 10)),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    "reg_depth": list(range(1, 21)),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    "min_samples_leaf": list(range(1, 21)),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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}

            


            
                                                                                                            
                            
            
                                    
            
            

                
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hyper = Hyperactive()

            


            
                                                                                                            
                            
            
                                    
            
            

                
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hyper.add_search(model, search_space, n_iter=10)

            


            
                                                                                                            
                                                                
            
                                    
            
            

                
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hyper.run()

            


            
                                                        
            
                                    
            
            

                
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