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pythonpandasclassificationsklearn-pandas

Unknown label type: (array([0. , 0.01..])) while using GaussianNB

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)

Throwing the error :

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.  ]),)
Solution

    1. first of all, you can refer to the documentation of sklearn here

    2. As per your array it looks like you're having continuous values so this model might not work for you, try switching to good old linear regression or RandomForestRegressor or whatever floats your boat.