本文整理汇总了Python中sklearn.neural_network.MLPClassifier.get_params方法的典型用法代码示例。如果您正苦于以下问题：Python MLPClassifier.get_params方法的具体用法？Python MLPClassifier.get_params怎么用？Python MLPClassifier.get_params使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sklearn.neural_network.MLPClassifier的用法示例。
在下文中一共展示了MLPClassifier.get_params方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: main
# 需要导入模块: from sklearn.neural_network import MLPClassifier [as 别名]
# 或者: from sklearn.neural_network.MLPClassifier import get_params [as 别名]
def main():
np.random.seed(RANDOM_STATE)
pd.set_option('display.width', 0)
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
data = pd.read_csv('data/train.csv')
#test_data = pd.read_csv('data/test.csv')
records = []
#n = 42000*0.8
n = 10000
X, y = extract_data(data, n)
activation = 'tanh'
param_dict = {'batch_size': [100, 200], 'momentum': [0.9, 0.99 ], 'learning_rate_init':[0.001, 0.01, 0.1]}
#param_dict = {'batch_size': [200], 'momentum': [0.9], 'learning_rate_init':[0.1]}
for param in ParameterGrid(param_dict):
nn = MLPClassifier(algorithm='sgd',
tol=float('-inf'),
warm_start = True,
max_iter=1,
hidden_layer_sizes = [200],
random_state=RANDOM_STATE)
#nn_params = {'algorithm': 'sgd', 'tol': float
nn_params = nn.get_params()
nn_params.update(param)
nn.set_params(**nn_params)
#nn = MLPClassifier(**nn_params)
time_limits = list(range(1, 60, 60))
try:
evaluation_list = trainer_by_time(X, y, time_limits, nn)
except:
evaluation_list = [{}]
for i in range(len(evaluation_list)):
evaluation = evaluation_list[i]
record = {}
record['n'] = n
record['time limit'] = time_limits[i]
record.update(evaluation)
record.update(param)
records.append(record)
df = pd.DataFrame(records)
cols = list(df.columns)
keys = evaluation_list[0].keys()
cols = [item for item in cols if item not in keys]
cols += keys
df = df.reindex(columns=cols)
now = datetime.datetime.now()
result_file = open('result.txt', 'a')
print(now,file=result_file)
print(df)
print(df,file=result_file)