未知标签类型:(array([0.， 0.01.]))，而使用高斯annb

Question

import pandas as pd
df = pd.read_csv("Test_data.csv")
df.head()
target = df.dst_host_srv_rerror_rate
inputs = df.drop('dst_host_srv_rerror_rate',axis='columns')
from sklearn.model_selection import train_test_split
X_train , X_test , Y_train , Y_test = train_test_split(inputs , target , test_size=0.3)
from sklearn.naive_bayes import GaussianNB
model = GaussianNB()
model.fit(X_train,Y_train)

抛出错误:

ValueError: Unknown label type: (array([0.  , 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1 ,
0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.2 , 0.21,
0.22, 0.23, 0.24, 0.25, 0.26, 0.27, 0.28, 0.29, 0.3 , 0.31, 0.32,
0.33, 0.34, 0.35, 0.36, 0.37, 0.38, 0.39, 0.4 , 0.41, 0.42, 0.43,
0.44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5 , 0.51, 0.52, 0.53, 0.54,
0.55, 0.56, 0.57, 0.58, 0.59, 0.6 , 0.61, 0.62, 0.63, 0.64, 0.65,
0.66, 0.67, 0.68, 0.69, 0.7 , 0.71, 0.72, 0.73, 0.74, 0.75, 0.76,
0.77, 0.78, 0.79, 0.8 , 0.81, 0.82, 0.83, 0.84, 0.85, 0.86, 0.87,
0.88, 0.89, 0.9 , 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98,
1.  ]),)

Answer 1

1. 首先，您可以参考此处的sklearn文档

2. 根据你的数组，它看起来像你有连续的值，所以这个模型可能不适合你，尝试切换到好的旧线性回归或RandomForestRegressor或任何漂浮你的船。