space
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(alpha=1.0, hidden_layer_sizes=30,
                               max_iter=1000000000000, random_state=123,
                               solver='lbfgs'))])

product
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(activation='tanh', alpha=1.0,
                               hidden_layer_sizes=20, max_iter=1000000000000,
                               random_state=123, solver='lbfgs'))])

rrs
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(alpha=1.0, hidden_layer_sizes=20,
                               max_iter=1000000000000, random_state=123,
                               solver='lbfgs'))])

satellite
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(activation='logistic', alpha=1.0,
                               hidden_layer_sizes=40, max_iter=1000000000000,
                               random_state=123, solver='lbfgs'))])

allfeat
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(activation='tanh', alpha=1.0,
                               hidden_layer_sizes=30, max_iter=1000000000000,
                               random_state=123, solver='lbfgs'))])

sst
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(alpha=0.01, hidden_layer_sizes=40,
                               max_iter=1000000000000, random_state=123,
                               solver='lbfgs'))])

chl
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(activation='logistic', alpha=0.1,
                               hidden_layer_sizes=10, max_iter=1000000000000,
                               random_state=123, solver='lbfgs'))])

par
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(hidden_layer_sizes=20, max_iter=1000000000000,
                               random_state=123, solver='lbfgs'))])

duo
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(activation='logistic', alpha=0.01,
                               hidden_layer_sizes=30, max_iter=1000000000000,
                               random_state=123, solver='lbfgs'))])

trio
Best estimator:
Pipeline(steps=[('sc', StandardScaler()),
                ('ml',
                 MLPClassifier(activation='tanh', alpha=0.1,
                               hidden_layer_sizes=10, max_iter=1000000000000,
                               random_state=123, solver='lbfgs'))])