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tests.test_methods.test_get_results()   A

↳ Parent: tests.test_methods

Complexity

Conditions 1

Size

Total Lines 8
Code Lines 7

Duplication

Lines 0
Ratio 0 %

Importance

Changes 0
Metric Value
eloc 7
dl 0
loc 8
rs 10
c 0
b 0
f 0
cc 1
nop 0
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# Author: Simon Blanke
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# Email: [email protected]
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# License: MIT License
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from sklearn.datasets import load_iris

            


            
                                                                                                            
                            
            
                                    
            
            

                
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from sklearn.model_selection import cross_val_score

            


            
                                                                                                            
                            
            
                                    
            
            

                
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from sklearn.tree import DecisionTreeClassifier

            


            
                                                                                                            
                            
            
                                    
            
            

                
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from hyperactive import Hyperactive

            


            
                                                                                                            
                            
            
                                    
            
            

                
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data = load_iris()

            


            
                                                                                                            
                            
            
                                    
            
            

                
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X = data.data

            


            
                                                                                                            
                            
            
                                    
            
            

                
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y = data.target

            


            
                                                                                                            
                            
            
                                    
            
            

                
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n_iter = 1

            


            
                                                                                                            
                            
            
                                    
            
            

                
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def model(para, X_train, y_train):

            


                            

                    
                        
                    
                    
                    
                    
                                                                                                    
                        

                            
                            
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    model = DecisionTreeClassifier(

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        criterion=para["criterion"],

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        max_depth=para["max_depth"],

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        min_samples_split=para["min_samples_split"],

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        min_samples_leaf=para["min_samples_leaf"],

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    )

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    scores = cross_val_score(model, X_train, y_train, cv=2)

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    return scores.mean()

            


            
                                                                                                            
                            
            
                                    
            
            

                
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search_config = {

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    model: {

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        "criterion": ["gini", "entropy"],

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        "max_depth": range(1, 11),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        "min_samples_split": range(2, 11),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        "min_samples_leaf": range(1, 11),

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    }

            


            
                                                                                                            
                            
            
                                    
            
            

                
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}

            


            
                                                                                                            
                            
            
                                    
            
            

                
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def test_get_results():

            


            
                                                        
            
                                    
            
            

                
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    opt = Hyperactive(search_config, n_iter=n_iter, optimizer="HillClimbing")

            


            
                                                        
            
                                    
            
            

                
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    opt.search(X, y)

            


            
                                                        
            
                                    
            
            

                
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    opt.get_results()

            


            
                                                        
            
                                    
            
            

                
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    opt = Hyperactive(search_config, n_iter=n_iter, n_jobs=2, optimizer="HillClimbing")

            


            
                                                        
            
                                    
            
            

                
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    opt.search(X, y)

            


            
                                                        
            
                                    
            
            

                
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    opt.get_results()

            


            
                                                        
            
                                    
            
            

                
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