pipeA = Pipeline([('Scale',StandardScaler()),
('KNN',knnC())])
pipeW = Pipeline([('Scale',StandardScaler()),
('KNN',knnC())])
params_wine= {'KNN__metric':['manhattan','euclidean','chebyshev'],'KNN__n_neighbors':np.arange(1,51,5),'KNN__weights':['uniform','distance']}
params_adult= {'KNN__metric':['manhattan','euclidean','chebyshev'],'KNN__n_neighbors':np.arange(1,51,5),'KNN__weights':['uniform','distance']}
#
start = time.time()
wine_clf = basicResults(pipeW,wine_trnX,wine_trnY,wine_tstX,wine_tstY,params_wine,'KNN','wine')
end = time.time()
print(end-start)
start = time.time()
adult_clf = basicResults(pipeA,adult_trnX,adult_trnY,adult_tstX,adult_tstY,params_adult,'KNN','adult')
end = time.time()
print(end-start)
start = time.time()
wine_final_params=wine_clf.best_params_
adult_final_params=adult_clf.best_params_
pipeW.set_params(**wine_final_params)
makeTimingCurve(wineX,wineY,pipeW,'KNN','wine')
pipeA.set_params(**adult_final_params)
makeTimingCurve(adultX,adultY,pipeA,'KNN','adult')
print(end-start)
curve_train_scores.to_csv('./output/{}_{}_LC_train.csv'.format(clf_type,dataset))
curve_test_scores.to_csv('./output/{}_{}_LC_test.csv'.format(clf_type,dataset))
end = time.time()
#print(end-start)
adult_clf = cv
#start = time.time()
wine_final_params = wine_clf.best_params_
wine_OF_params = wine_final_params.copy()
wine_OF_params['SVM__alpha'] = 1e-16
adult_final_params =adult_clf.best_params_
adult_OF_params = adult_final_params.copy()
adult_OF_params['SVM__alpha'] = 1e-16
pipeW.set_params(**wine_final_params)
makeTimingCurve(wineX,wineY,pipeW,'SVM_RBF','wine')
pipeA.set_params(**adult_final_params)
makeTimingCurve(adultX,adultY,pipeW,'SVM_RBF','adult')
pipeW.set_params(**wine_final_params)
iterationLC(pipeW,wine_trnX,wine_trnY,wine_tstX,wine_tstY,{'SVM__n_iter':[2**x for x in range(12)]},'SVM_RBF','wine')
pipeA.set_params(**adult_final_params)
iterationLC(pipeA,adult_trnX,adult_trnY,adult_tstX,adult_tstY,{'SVM__n_iter':np.arange(1,75,3)},'SVM_RBF','adult')
pipeA.set_params(**adult_OF_params)
iterationLC(pipeA,adult_trnX,adult_trnY,adult_tstX,adult_tstY,{'SVM__n_iter':np.arange(1,75,3)},'SVM_RBF_OF','adult')
pipeW.set_params(**wine_OF_params)
iterationLC(pipeW,wine_trnX,wine_trnY,wine_tstX,wine_tstY,{'SVM__n_iter':np.arange(100,2600,100)},'SVM_RBF_OF','wine')
end = time.time()
print(end-start)