Python 返回未知 label 类型：(array([0., 0., 0., ..., 0., 0., 0.]),)

Question

我在运行下面的代码时遇到了麻烦，他应该适合训练预测器和训练 class。 我知道现在发生了什么，我尝试调试但我没有得到任何回报，似乎问题来自我的这段代码：

我认为的问题

from sklearn.neural_network import MLPClassifier
classificador = MLPClassifier(verbose = True,
                              max_iter=1000,
                              tol = 0.0000010,
                              solver = 'adam',
                              hidden_layer_sizes=(100),
                              activation='relu')
classificador.fit(previsores_treinamento, classe_treinamento)
previsoes = classificador.predict(previsores_teste)

这是我的所有代码：

import pandas as pd
import numpy as np

base = pd.read_csv("credit_data.csv")
base.loc[base['age'] < 0] = 40.92 

previsores = base.iloc[:,1:4].values
classe = base.iloc[:,4].values

from sklearn.impute import SimpleImputer 
imputer = SimpleImputer(missing_values = np.nan, strategy = 'mean')
imputer = imputer.fit(previsores[:, 1:4])
previsores[:, 1:4] = imputer.transform(previsores[:, 1:4])

from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
previsores = scaler.fit_transform(previsores)

from sklearn.model_selection import train_test_split
previsores_treinamento, previsores_teste, classe_treinamento, classe_teste = train_test_split(previsores, classe, test_size=0.25,random_state=0)

from sklearn.neural_network import MLPClassifier
classificador = MLPClassifier(verbose = True,
                              max_iter=1000,
                              tol = 0.0000010,
                              solver = 'adam',
                              hidden_layer_sizes=(100),
                              activation='relu')
classificador.fit(previsores_treinamento, classe_treinamento)
previsoes = classificador.predict(previsores_teste)