gridsearchCV result score가 동일하게 나옵니다.
미해결
import numpy from sklearn . model_selection import GridSearchCV from keras . models import Sequential from keras . layers import Dense from keras . wrappers . scikit_learn import KerasClassifier #load data data = pd.read_csv('~/all.csv') df - data.iloc[:, 4:] X = pd.DataFrame(df.values) Y = pd.DataFrame(data, columns=['number']) X_train, X_test, Y_train, Y_test = train_test_split(X.values, Y.values, test_size=0.1, random_state=42) # Function to create model, required for KerasClassifier def create_model (neurons=256 ) : # create model model = Sequential ( ) model . add ( Dense (neurons , input_dim =8192 , activation = 'sigmoid' ) ) model . add ( Dense (neurons , activation = 'sigmoid' ) ) model . add ( Dense (neurons , activation = 'sigmoid' ) ) model . add ( Dense (neurons , activation = 'sigmoid' ) ) model . add ( Dense (1 , activation = 'linear' ) ) # Compile model model . compile ( loss = 'mae' , optimizer = 'adam' ) return model # fix random seed for reproducibility seed = 7 numpy . random . seed ( seed ) model = KerasClassifier ( build_fn = create_model , verbose = 0, batch_size = 8 ) # define the grid search parameters neurons = [ 256 ] epochs = [ 32, 64 ] param_grid = dict ( neurons=neurons , epochs = epochs ) grid = GridSearchCV ( estimator = model , param_grid = param_grid , n_jobs = - 1 , cv = 3, scoring='r2' ) grid_result = grid . fit ( X_train , Y_train ) # summarize results print ( "Best: %f using %s" % ( grid_result . best_score_ , grid_result . best_params_ ) ) means = grid_result . cv_results_ [ 'mean_test_score' ] stds = grid_result . cv_results_ [ 'std_test_score' ] params = grid_result . cv_results_ [ 'params' ] for mean , stdev , param in zip ( means , stds , params ) : print ( "%f (%f) with: %r" % ( mean , stdev , param ) ) 코드입니다. 이렇게 실행시키면 결과값이 모두 동일한 값이 나와요. Best: -16.710561 using {'epochs': 32, 'neurons': 256} -16.710561 (5.419502) with {'epochs': 32, 'neurons': 256} -16.710561 (5.419502) with {'epochs': 64, 'neurons': 256} 위 값 뿐만아니라 mean_test_socre 등 모든 값이 동일하게 나와 최적의 parameter를 구할수 없습니다. 무엇이 문제인지 알려주세요.
- python
- gridsearch
- gridsearchcv